This version of the adiposity analysis mirrors the birth weight analysis from 09_NPB_Model_BW_v4_MD.R
Some key findings to note:
The HS data set was previously used in the CEI paper (Martenies et al., 2019). In the original analysis, we used an exposure index based on the CalEnvironScreen tool. We observed lower birth weights and lower adiposity associated with higher index scores, driven largely by exposures to social indicators of health at the neighborhood level. Now, we are aiming to use methods for mixtures to try to identify which exposures are driving these association.
The complete data set for the adiposity outcome consists of n = 780 participants. This represents 67.77% of the original Healthy Start 1 cohort.
Of the 780 participants, 0.26% identify as Latina, 0.17% identify as Black, and 0.26% identify as another non-NHW race or ethnicity. The median age of mothers in this dataset is 28 years. 0.51% of babies born were male.
We have included 20 exposures in our analysis.
These exposures are based on the census tract where each mother lived at the time of enrollment into Healthy Start. With the exception of air pollution (mean_pm and mean_o3), these are based on long-term averages at for each census tract. For mean_pm and mean_o3 are based on the average pollution levels across each pregnancy (est. conception date to delivery date) estimated using ordinary kriging and monitoring data.
#' Exposure data
X <- select(hs_data2, mean_pm, mean_o3, mean_temp, pct_tree_cover, pct_impervious,
mean_aadt_intensity, dist_m_tri:dist_m_mine_well,
cvd_rate_adj, res_rate_adj, violent_crime_rate, property_crime_rate,
pct_less_hs, pct_unemp, pct_limited_eng, pct_hh_pov, pct_poc) %>%
as.matrix()
head(X)
## mean_pm mean_o3 mean_temp pct_tree_cover pct_impervious
## [1,] 8.483046 47.19072 51.81487 6.006276 43.30893
## [2,] 6.598608 50.05090 58.32885 7.281109 48.36432
## [3,] 7.454146 48.57052 58.01924 17.205991 31.67281
## [4,] 6.671239 50.06429 61.35590 6.842898 45.00359
## [5,] 7.122537 50.14275 59.28421 3.357792 28.16745
## [6,] 7.637453 47.03125 55.32825 10.743612 45.87564
## mean_aadt_intensity dist_m_tri dist_m_npl dist_m_waste_site
## [1,] 10128.4962 2827.538 729.2371 4829.780
## [2,] 10749.0359 1576.420 5239.2211 4417.792
## [3,] 9048.6468 3350.303 2992.2968 5211.871
## [4,] 4223.3434 3364.954 6998.1286 8921.318
## [5,] 858.7283 2923.811 3427.2247 7006.042
## [6,] 15603.9800 3364.200 3166.5395 4484.960
## dist_m_major_emit dist_m_cafo dist_m_mine_well cvd_rate_adj res_rate_adj
## [1,] 7968.654 29116.58 1749.1256 275.2480 155.7767
## [2,] 3780.951 51044.30 7354.5310 279.6435 226.8038
## [3,] 7423.232 36079.21 4887.2996 221.0414 157.6974
## [4,] 9636.816 42235.78 3752.6399 203.8812 142.5368
## [5,] 6806.912 29145.98 729.7784 194.1983 101.0046
## [6,] 5265.285 43921.85 5870.6867 174.3361 120.3281
## violent_crime_rate property_crime_rate pct_less_hs pct_unemp
## [1,] 14.377133 37.32935 31.784946 11.529628
## [2,] 8.905404 67.03932 15.290231 4.908306
## [3,] 7.636888 46.78194 6.891702 4.564963
## [4,] 2.850212 21.95270 2.725915 5.623583
## [5,] 5.435988 22.49834 12.919186 5.234103
## [6,] 5.035971 47.15500 3.842365 10.000000
## pct_limited_eng pct_hh_pov pct_poc
## [1,] 26.114650 12.010919 90.33703
## [2,] 8.500401 18.123496 30.44025
## [3,] 0.000000 6.307978 26.63305
## [4,] 1.350621 9.292274 32.68648
## [5,] 6.307385 2.115768 73.60772
## [6,] 5.121799 25.171768 23.08698
Variance and histograms of the exposure variables (in their original units):
var(X)
## mean_pm mean_o3 mean_temp pct_tree_cover
## mean_pm 0.387935651 -0.006062324 0.08159322 -0.24186797
## mean_o3 -0.006062324 8.955071063 10.91751296 -0.42975173
## mean_temp 0.081593216 10.917512965 19.07709741 0.42247728
## pct_tree_cover -0.241867968 -0.429751728 0.42247728 10.14239201
## pct_impervious 0.374669222 -1.022666581 4.17459123 7.01532904
## mean_aadt_intensity -244.348900205 303.692966735 2560.03377531 9016.25164719
## dist_m_tri -262.436608185 331.077954338 -912.79043355 -208.41963901
## dist_m_npl -323.917936386 588.917794378 -131.31485219 165.47445225
## dist_m_waste_site -255.868380544 139.101947771 -108.57465114 1967.86242644
## dist_m_major_emit 54.696478097 795.943835213 362.18792432 109.80052618
## dist_m_cafo -1416.446418998 -161.908280851 105.15291800 10579.76974425
## dist_m_mine_well -346.805134977 -503.738613039 -365.87801373 3305.89212551
## cvd_rate_adj 3.764074301 4.075840732 10.83290159 -24.37524733
## res_rate_adj 1.965274289 1.428149656 9.57543380 -1.41491470
## violent_crime_rate 0.155877411 0.749569861 1.11397496 -3.73949960
## property_crime_rate 1.705778861 -1.922286944 5.72267156 -21.72665992
## pct_less_hs 1.150349004 1.853281484 1.91377595 -7.56529205
## pct_unemp 0.055091002 0.506543293 0.44701628 -0.09840703
## pct_limited_eng 0.412512233 1.029344921 0.81158219 -2.79407307
## pct_hh_pov 0.606596961 0.246447334 1.69567408 0.62423227
## pct_poc 1.697984717 3.441448054 2.04851012 -19.39024560
## pct_impervious mean_aadt_intensity dist_m_tri
## mean_pm 0.3746692 -244.3489 -262.4366
## mean_o3 -1.0226666 303.6930 331.0780
## mean_temp 4.1745912 2560.0338 -912.7904
## pct_tree_cover 7.0153290 9016.2516 -208.4196
## pct_impervious 179.3785613 56186.2650 -16125.7853
## mean_aadt_intensity 56186.2649588 69165922.5363 -1545741.2032
## dist_m_tri -16125.7853155 -1545741.2032 6796986.1348
## dist_m_npl -9073.4066413 1215685.3718 4579262.3957
## dist_m_waste_site -5149.3668557 1813109.3670 2501094.5398
## dist_m_major_emit 2552.7325419 2477044.2166 1636072.5435
## dist_m_cafo 17731.4297754 15642123.4910 3145985.3646
## dist_m_mine_well 1088.8996239 2146886.0916 937920.3657
## cvd_rate_adj 238.2585184 20288.9695 -51713.8246
## res_rate_adj 182.9073227 34962.3596 -32708.1468
## violent_crime_rate 23.5426763 4766.3910 -848.4942
## property_crime_rate 96.9554914 18227.6819 -3222.6487
## pct_less_hs 59.7110274 -3644.3902 -12701.6695
## pct_unemp 25.7808764 5880.6527 -2452.4569
## pct_limited_eng 42.8626714 2701.0340 -5437.8035
## pct_hh_pov 84.0422503 18597.5270 -8881.9880
## pct_poc 89.6891621 4493.4912 -18654.6550
## dist_m_npl dist_m_waste_site dist_m_major_emit
## mean_pm -323.9179 -255.8684 54.69648
## mean_o3 588.9178 139.1019 795.94384
## mean_temp -131.3149 -108.5747 362.18792
## pct_tree_cover 165.4745 1967.8624 109.80053
## pct_impervious -9073.4066 -5149.3669 2552.73254
## mean_aadt_intensity 1215685.3718 1813109.3670 2477044.21655
## dist_m_tri 4579262.3957 2501094.5398 1636072.54352
## dist_m_npl 11347069.4851 4199731.9447 7041775.87881
## dist_m_waste_site 4199731.9447 5299321.7913 1350703.22559
## dist_m_major_emit 7041775.8788 1350703.2256 10385263.63290
## dist_m_cafo 4931146.1458 5617993.1230 -3395813.15490
## dist_m_mine_well 258232.8698 1384614.0282 -1787310.96945
## cvd_rate_adj -33265.8693 -43188.0097 15096.48910
## res_rate_adj -19718.2591 -31937.2229 -1526.60012
## violent_crime_rate -152.7587 -3204.3439 461.39386
## property_crime_rate -14876.4444 -19362.3191 -20045.85330
## pct_less_hs -6945.0281 -11539.8973 8548.88251
## pct_unemp 2139.2957 -1457.5039 5159.73353
## pct_limited_eng 432.5398 -4292.4445 9331.34328
## pct_hh_pov -1451.6169 -7730.1917 8680.72868
## pct_poc -2074.8078 -8515.4005 21998.02980
## dist_m_cafo dist_m_mine_well cvd_rate_adj res_rate_adj
## mean_pm -1416.4464 -346.8051 3.764074 1.965274
## mean_o3 -161.9083 -503.7386 4.075841 1.428150
## mean_temp 105.1529 -365.8780 10.832902 9.575434
## pct_tree_cover 10579.7697 3305.8921 -24.375247 -1.414915
## pct_impervious 17731.4298 1088.8996 238.258518 182.907323
## mean_aadt_intensity 15642123.4910 2146886.0916 20288.969539 34962.359641
## dist_m_tri 3145985.3646 937920.3657 -51713.824619 -32708.146822
## dist_m_npl 4931146.1458 258232.8698 -33265.869348 -19718.259098
## dist_m_waste_site 5617993.1230 1384614.0282 -43188.009668 -31937.222912
## dist_m_major_emit -3395813.1549 -1787310.9695 15096.489101 -1526.600117
## dist_m_cafo 46839423.7820 9553723.7226 -44601.199501 -7797.531774
## dist_m_mine_well 9553723.7226 4464054.8852 -38076.395520 -14953.132358
## cvd_rate_adj -44601.1995 -38076.3955 2076.657134 1315.804108
## res_rate_adj -7797.5318 -14953.1324 1315.804108 1110.806026
## violent_crime_rate 408.3455 -2058.0613 134.891314 100.535111
## property_crime_rate -18380.9466 -4567.0382 320.604924 290.157212
## pct_less_hs -24463.8379 -9889.2545 334.637464 201.489440
## pct_unemp -416.0610 -2620.4519 105.334428 74.963887
## pct_limited_eng -6285.3923 -4618.3890 185.226339 106.490953
## pct_hh_pov 252.0453 -4667.4525 269.033064 206.556606
## pct_poc -42540.4506 -24578.3527 619.542560 300.056264
## violent_crime_rate property_crime_rate pct_less_hs
## mean_pm 0.1558774 1.705779 1.150349
## mean_o3 0.7495699 -1.922287 1.853281
## mean_temp 1.1139750 5.722672 1.913776
## pct_tree_cover -3.7394996 -21.726660 -7.565292
## pct_impervious 23.5426763 96.955491 59.711027
## mean_aadt_intensity 4766.3910356 18227.681901 -3644.390223
## dist_m_tri -848.4941529 -3222.648703 -12701.669456
## dist_m_npl -152.7586849 -14876.444381 -6945.028107
## dist_m_waste_site -3204.3438644 -19362.319083 -11539.897288
## dist_m_major_emit 461.3938611 -20045.853299 8548.882507
## dist_m_cafo 408.3455047 -18380.946611 -24463.837868
## dist_m_mine_well -2058.0613390 -4567.038163 -9889.254521
## cvd_rate_adj 134.8913140 320.604924 334.637464
## res_rate_adj 100.5351114 290.157212 201.489440
## violent_crime_rate 36.5195077 135.346154 25.285073
## property_crime_rate 135.3461545 1160.236223 3.004961
## pct_less_hs 25.2850735 3.004961 163.762734
## pct_unemp 12.0566338 3.018063 40.254624
## pct_limited_eng 14.1433364 -11.409839 86.491751
## pct_hh_pov 30.5537434 63.667397 103.102830
## pct_poc 52.0085020 -26.369164 241.514049
## pct_unemp pct_limited_eng pct_hh_pov pct_poc
## mean_pm 0.05509100 0.4125122 0.6065970 1.697985
## mean_o3 0.50654329 1.0293449 0.2464473 3.441448
## mean_temp 0.44701628 0.8115822 1.6956741 2.048510
## pct_tree_cover -0.09840703 -2.7940731 0.6242323 -19.390246
## pct_impervious 25.78087638 42.8626714 84.0422503 89.689162
## mean_aadt_intensity 5880.65274910 2701.0340348 18597.5269669 4493.491248
## dist_m_tri -2452.45686782 -5437.8034938 -8881.9879579 -18654.655039
## dist_m_npl 2139.29571806 432.5397585 -1451.6169481 -2074.807832
## dist_m_waste_site -1457.50390263 -4292.4445272 -7730.1916796 -8515.400484
## dist_m_major_emit 5159.73353103 9331.3432771 8680.7286763 21998.029803
## dist_m_cafo -416.06100829 -6285.3922771 252.0452517 -42540.450615
## dist_m_mine_well -2620.45185414 -4618.3890431 -4667.4524666 -24578.352704
## cvd_rate_adj 105.33442831 185.2263391 269.0330637 619.542560
## res_rate_adj 74.96388699 106.4909525 206.5566058 300.056264
## violent_crime_rate 12.05663378 14.1433364 30.5537434 52.008502
## property_crime_rate 3.01806326 -11.4098394 63.6673970 -26.369164
## pct_less_hs 40.25462427 86.4917511 103.1028300 241.514049
## pct_unemp 24.70089342 25.8002340 37.9257486 73.691783
## pct_limited_eng 25.80023399 69.4638469 69.0402541 143.757101
## pct_hh_pov 37.92574856 69.0402541 122.9753676 158.037277
## pct_poc 73.69178348 143.7571008 158.0372769 530.391699
ggplot(pivot_longer(as.data.frame(X), mean_pm:pct_poc, names_to = "exp", values_to = "value")) +
geom_histogram(aes(x = value)) +
facet_wrap(~ exp, scales = "free")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Scaling the exposure variables
X.scaled <- apply(X, 2, scale)
head(X.scaled)
## mean_pm mean_o3 mean_temp pct_tree_cover pct_impervious
## [1,] 1.63895222 -0.2235917 -0.1608519 -0.09106707 0.2355128
## [2,] -1.38658135 0.7321879 1.3305352 0.30923073 0.6129716
## [3,] -0.01298527 0.2374938 1.2596504 3.42564459 -0.6332930
## [4,] -1.26996939 0.7366655 2.0235840 0.17163233 0.3620440
## [5,] -0.54539411 0.7628814 1.5492657 -0.92269126 -0.8950193
## [6,] 0.28132089 -0.2768817 0.6435419 1.39645679 0.4271554
## mean_aadt_intensity dist_m_tri dist_m_npl dist_m_waste_site
## [1,] -0.004372722 -0.3966655 -1.41524068 -0.158944386
## [2,] 0.070241827 -0.8765539 -0.07638689 -0.337912010
## [3,] -0.134215290 -0.1961498 -0.74341877 0.007035929
## [4,] -0.714416377 -0.1905302 0.44577016 1.618419775
## [5,] -1.118982302 -0.3597382 -0.61430417 0.786424074
## [6,] 0.654006942 -0.1908194 -0.69169232 -0.308734136
## dist_m_major_emit dist_m_cafo dist_m_mine_well cvd_rate_adj res_rate_adj
## [1,] -0.09829063 -1.1211055 -0.7694006 0.6888535 -0.2667071
## [2,] -1.39776302 2.0828583 1.8836300 0.7853085 1.8643986
## [3,] -0.26753873 -0.1037626 0.7158928 -0.5006603 -0.2090789
## [4,] 0.41935153 0.7958031 0.1788599 -0.8772257 -0.6639585
## [5,] -0.45878682 -1.1168106 -1.2518563 -1.0897090 -1.9100974
## [6,] -0.93716429 1.0421630 1.1813285 -1.5255654 -1.3303122
## violent_crime_rate property_crime_rate pct_less_hs pct_unemp
## [1,] 0.2857705 -0.5116110 1.20006290 0.38269452
## [2,] -0.6196746 0.3606149 -0.08889067 -0.94956352
## [3,] -0.8295849 -0.2341017 -0.74518055 -1.01864671
## [4,] -1.6216694 -0.9630391 -1.07070943 -0.80564470
## [5,] -1.1937830 -0.9470203 -0.27417225 -0.88401077
## [6,] -1.2599766 -0.2231493 -0.98346622 0.07492226
## pct_limited_eng pct_hh_pov pct_poc
## [1,] 2.15729293 -0.2815741 1.5763100
## [2,] 0.04387831 0.2696336 -1.0244789
## [3,] -0.97602734 -0.7958425 -1.1897923
## [4,] -0.81397542 -0.5267306 -0.9269452
## [5,] -0.21924683 -1.1738791 0.8499036
## [6,] -0.36149732 0.9052185 -1.3437665
Variance and histograms of the exposure variables (scaled):
var(X.scaled)
## mean_pm mean_o3 mean_temp pct_tree_cover
## mean_pm 1.000000000 -0.003252556 0.029992872 -0.121934980
## mean_o3 -0.003252556 1.000000000 0.835281859 -0.045093393
## mean_temp 0.029992872 0.835281859 1.000000000 0.030372253
## pct_tree_cover -0.121934980 -0.045093393 0.030372253 1.000000000
## pct_impervious 0.044914121 -0.025516099 0.071362908 0.164472230
## mean_aadt_intensity -0.047172018 0.012202649 0.070476359 0.340415825
## dist_m_tri -0.161616753 0.042436304 -0.080159821 -0.025102111
## dist_m_npl -0.154387912 0.058422253 -0.008925157 0.015424777
## dist_m_waste_site -0.178454140 0.020192428 -0.010798468 0.268419703
## dist_m_major_emit 0.027250266 0.082535188 0.025731734 0.010698563
## dist_m_cafo -0.332287904 -0.007905490 0.003517705 0.485400532
## dist_m_mine_well -0.263536583 -0.079672044 -0.039647463 0.491307868
## cvd_rate_adj 0.132616005 0.029888236 0.054425979 -0.167956353
## res_rate_adj 0.094672580 0.014319244 0.065778383 -0.013330331
## violent_crime_rate 0.041413399 0.041449103 0.042204312 -0.194303596
## property_crime_rate 0.080402522 -0.018858645 0.038465330 -0.200285524
## pct_less_hs 0.144325222 0.048394870 0.034239499 -0.185629913
## pct_unemp 0.017796906 0.034058516 0.020592585 -0.006217268
## pct_limited_eng 0.079465308 0.041271190 0.022294459 -0.105266007
## pct_hh_pov 0.087823617 0.007426438 0.035008795 0.017675307
## pct_poc 0.118373795 0.049935378 0.020364962 -0.264371573
## pct_impervious mean_aadt_intensity dist_m_tri dist_m_npl
## mean_pm 0.04491412 -0.04717202 -0.16161675 -0.154387912
## mean_o3 -0.02551610 0.01220265 0.04243630 0.058422253
## mean_temp 0.07136291 0.07047636 -0.08015982 -0.008925157
## pct_tree_cover 0.16447223 0.34041583 -0.02510211 0.015424777
## pct_impervious 1.00000000 0.50442756 -0.46182497 -0.201114438
## mean_aadt_intensity 0.50442756 1.00000000 -0.07129064 0.043394356
## dist_m_tri -0.46182497 -0.07129064 1.00000000 0.521429359
## dist_m_npl -0.20111444 0.04339436 0.52142936 1.000000000
## dist_m_waste_site -0.16701613 0.09470388 0.41673672 0.541588668
## dist_m_major_emit 0.05914408 0.09242275 0.19473123 0.648681599
## dist_m_cafo 0.19344287 0.27481716 0.17631641 0.213894809
## dist_m_mine_well 0.03848024 0.12217945 0.17027191 0.036283143
## cvd_rate_adj 0.39037390 0.05353422 -0.43527735 -0.216707839
## res_rate_adj 0.40975731 0.12613498 -0.37642515 -0.175633598
## violent_crime_rate 0.29087615 0.09483772 -0.05385527 -0.007504152
## property_crime_rate 0.21252691 0.06434461 -0.03628955 -0.129653449
## pct_less_hs 0.34838683 -0.03424296 -0.38071069 -0.161110784
## pct_unemp 0.38730765 0.14227321 -0.18927221 0.127782869
## pct_limited_eng 0.38398526 0.03896768 -0.25025681 0.015406527
## pct_hh_pov 0.56585263 0.20165084 -0.30721536 -0.038859849
## pct_poc 0.29077451 0.02346062 -0.31069243 -0.026744696
## dist_m_waste_site dist_m_major_emit dist_m_cafo
## mean_pm -0.17845414 0.02725027 -0.332287904
## mean_o3 0.02019243 0.08253519 -0.007905490
## mean_temp -0.01079847 0.02573173 0.003517705
## pct_tree_cover 0.26841970 0.01069856 0.485400532
## pct_impervious -0.16701613 0.05914408 0.193442865
## mean_aadt_intensity 0.09470388 0.09242275 0.274817163
## dist_m_tri 0.41673672 0.19473123 0.176316410
## dist_m_npl 0.54158867 0.64868160 0.213894809
## dist_m_waste_site 1.00000000 0.18207111 0.356586819
## dist_m_major_emit 0.18207111 1.00000000 -0.153967569
## dist_m_cafo 0.35658682 -0.15396757 1.000000000
## dist_m_mine_well 0.28467794 -0.26249836 0.660696709
## cvd_rate_adj -0.41169031 0.10279803 -0.143007353
## res_rate_adj -0.41626308 -0.01421338 -0.034184739
## violent_crime_rate -0.23033849 0.02369194 0.009873237
## property_crime_rate -0.24693009 -0.18261758 -0.078847675
## pct_less_hs -0.39172768 0.20729701 -0.279325946
## pct_unemp -0.12739232 0.32215300 -0.012231928
## pct_limited_eng -0.22372532 0.34742094 -0.110191273
## pct_hh_pov -0.30281059 0.24290606 0.003320960
## pct_poc -0.16061887 0.29639895 -0.269896936
## dist_m_mine_well cvd_rate_adj res_rate_adj
## mean_pm -0.26353658 0.13261601 0.09467258
## mean_o3 -0.07967204 0.02988824 0.01431924
## mean_temp -0.03964746 0.05442598 0.06577838
## pct_tree_cover 0.49130787 -0.16795635 -0.01333033
## pct_impervious 0.03848024 0.39037390 0.40975731
## mean_aadt_intensity 0.12217945 0.05353422 0.12613498
## dist_m_tri 0.17027191 -0.43527735 -0.37642515
## dist_m_npl 0.03628314 -0.21670784 -0.17563360
## dist_m_waste_site 0.28467794 -0.41169031 -0.41626308
## dist_m_major_emit -0.26249836 0.10279803 -0.01421338
## dist_m_cafo 0.66069671 -0.14300735 -0.03418474
## dist_m_mine_well 1.00000000 -0.39546556 -0.21234806
## cvd_rate_adj -0.39546556 1.00000000 0.86634271
## res_rate_adj -0.21234806 0.86634271 1.00000000
## violent_crime_rate -0.16118740 0.48982295 0.49915588
## property_crime_rate -0.06345950 0.20654495 0.25558834
## pct_less_hs -0.36575582 0.57383181 0.47241713
## pct_unemp -0.24954857 0.46508423 0.45256051
## pct_limited_eng -0.26226862 0.48768672 0.38336652
## pct_hh_pov -0.19920768 0.53237076 0.55887015
## pct_poc -0.50511428 0.59032393 0.39091760
## violent_crime_rate property_crime_rate pct_less_hs
## mean_pm 0.041413399 0.08040252 0.14432522
## mean_o3 0.041449103 -0.01885865 0.04839487
## mean_temp 0.042204312 0.03846533 0.03423950
## pct_tree_cover -0.194303596 -0.20028552 -0.18562991
## pct_impervious 0.290876145 0.21252691 0.34838683
## mean_aadt_intensity 0.094837724 0.06434461 -0.03424296
## dist_m_tri -0.053855270 -0.03628955 -0.38071069
## dist_m_npl -0.007504152 -0.12965345 -0.16111078
## dist_m_waste_site -0.230338488 -0.24693009 -0.39172768
## dist_m_major_emit 0.023691938 -0.18261758 0.20729701
## dist_m_cafo 0.009873237 -0.07884767 -0.27932595
## dist_m_mine_well -0.161187402 -0.06345950 -0.36575582
## cvd_rate_adj 0.489822949 0.20654495 0.57383181
## res_rate_adj 0.499155881 0.25558834 0.47241713
## violent_crime_rate 1.000000000 0.65752195 0.32695970
## property_crime_rate 0.657521947 1.00000000 0.00689379
## pct_less_hs 0.326959697 0.00689379 1.00000000
## pct_unemp 0.401427649 0.01782784 0.63292450
## pct_limited_eng 0.280808338 -0.04019082 0.81093815
## pct_hh_pov 0.455924473 0.16855235 0.72653072
## pct_poc 0.373691766 -0.03361436 0.81947649
## pct_unemp pct_limited_eng pct_hh_pov pct_poc
## mean_pm 0.017796906 0.07946531 0.087823617 0.11837380
## mean_o3 0.034058516 0.04127119 0.007426438 0.04993538
## mean_temp 0.020592585 0.02229446 0.035008795 0.02036496
## pct_tree_cover -0.006217268 -0.10526601 0.017675307 -0.26437157
## pct_impervious 0.387307652 0.38398526 0.565852631 0.29077451
## mean_aadt_intensity 0.142273206 0.03896768 0.201650845 0.02346062
## dist_m_tri -0.189272211 -0.25025681 -0.307215358 -0.31069243
## dist_m_npl 0.127782869 0.01540653 -0.038859849 -0.02674470
## dist_m_waste_site -0.127392321 -0.22372532 -0.302810585 -0.16061887
## dist_m_major_emit 0.322153000 0.34742094 0.242906063 0.29639895
## dist_m_cafo -0.012231928 -0.11019127 0.003320960 -0.26989694
## dist_m_mine_well -0.249548573 -0.26226862 -0.199207679 -0.50511428
## cvd_rate_adj 0.465084229 0.48768672 0.532370759 0.59032393
## res_rate_adj 0.452560508 0.38336652 0.558870145 0.39091760
## violent_crime_rate 0.401427649 0.28080834 0.455924473 0.37369177
## property_crime_rate 0.017827843 -0.04019082 0.168552353 -0.03361436
## pct_less_hs 0.632924498 0.81093815 0.726530718 0.81947649
## pct_unemp 1.000000000 0.62285635 0.688127265 0.64381987
## pct_limited_eng 0.622856353 1.00000000 0.746988474 0.74894777
## pct_hh_pov 0.688127265 0.74698847 1.000000000 0.61880258
## pct_poc 0.643819872 0.74894777 0.618802578 1.00000000
ggplot(pivot_longer(as.data.frame(X.scaled), mean_pm:pct_poc,
names_to = "exp", values_to = "value")) +
geom_histogram(aes(x = value)) +
facet_wrap(~ exp, scales = "free")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Covariates were assessed at the individual level. These were selected based on previous HS studies and others in the literature and informed by a DAG.
There are four continuous covariates; all of the others have been coded as dummy variables. For the dummy variables, the reference groups are: white_re, ed_grad, norm_bmi
W <- select(hs_data2,
lat, lon, lat_lon_int,
latina_re, black_re, other_re,
ed_no_hs, ed_hs, ed_aa, ed_4yr,
low_bmi, ovwt_bmi, obese_bmi,
concep_spring, concep_summer, concep_fall,
concep_2010, concep_2011, concep_2012, concep_2013,
maternal_age, any_smoker, smokeSH, mean_cpss, mean_epsd,
male, gest_age_w, days_to_peapod) %>%
as.matrix()
head(W)
## lat lon lat_lon_int latina_re black_re other_re ed_no_hs ed_hs
## [1,] 39.79402 -104.8133 -4170.944 1 0 0 0 0
## [2,] 39.62671 -104.9927 -4160.517 0 0 1 0 0
## [3,] 39.74934 -104.9129 -4170.219 0 0 0 0 0
## [4,] 39.68397 -104.8933 -4162.583 0 0 0 0 0
## [5,] 39.79134 -104.7669 -4168.814 0 1 0 0 0
## [6,] 39.68050 -104.9451 -4164.274 1 0 0 0 0
## ed_aa ed_4yr low_bmi ovwt_bmi obese_bmi concep_spring concep_summer
## [1,] 1 0 0 0 0 0 0
## [2,] 1 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0
## [4,] 1 0 0 0 0 1 0
## [5,] 0 1 0 0 0 1 0
## [6,] 1 0 0 0 0 0 0
## concep_fall concep_2010 concep_2011 concep_2012 concep_2013 maternal_age
## [1,] 0 0 0 0 0 19
## [2,] 0 1 0 0 0 36
## [3,] 0 1 0 0 0 34
## [4,] 0 1 0 0 0 28
## [5,] 0 1 0 0 0 30
## [6,] 0 1 0 0 0 22
## any_smoker smokeSH mean_cpss mean_epsd male gest_age_w days_to_peapod
## [1,] 0 1 29 0 0 40.57143 1
## [2,] 0 0 19 2 1 35.85714 2
## [3,] 0 0 19 1 0 40.42857 2
## [4,] 0 0 20 0 0 36.28571 1
## [5,] 0 0 15 0 1 38.42857 2
## [6,] 0 0 17 1 0 40.71429 1
Scaled the non-binary (continuous) covariates
colnames(W)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "gest_age_w" "days_to_peapod"
W.s <- apply(W[,c(1, 2, 3, 21, 24, 25, 27, 28)], 2, scale) #' just the continuous ones
W.scaled <- cbind(W.s[,1:3],
W[,4:20], W.s[,4],
W[,22:23], W.s[,5:6],
W[,26], W.s[,7:8])
colnames(W.scaled)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "" "gest_age_w" "days_to_peapod"
colnames(W.scaled) <- colnames(W)
head(W.scaled)
## lat lon lat_lon_int latina_re black_re other_re ed_no_hs
## [1,] 0.9582490 0.5369709 -0.5836483 1 0 0 0
## [2,] -1.5595136 -1.6096907 0.6608980 0 0 1 0
## [3,] 0.2858292 -0.6547167 -0.4971411 0 0 0 0
## [4,] -0.6978905 -0.4200223 0.4143032 0 0 0 0
## [5,] 0.9178908 1.0931096 -0.3293688 0 1 0 0
## [6,] -0.7500299 -1.0397812 0.2123849 1 0 0 0
## ed_hs ed_aa ed_4yr low_bmi ovwt_bmi obese_bmi concep_spring concep_summer
## [1,] 0 1 0 0 0 0 0 0
## [2,] 0 1 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0
## [4,] 0 1 0 0 0 0 1 0
## [5,] 0 0 1 0 0 0 1 0
## [6,] 0 1 0 0 0 0 0 0
## concep_fall concep_2010 concep_2011 concep_2012 concep_2013 maternal_age
## [1,] 0 0 0 0 0 -1.41994612
## [2,] 0 1 0 0 0 1.35302672
## [3,] 0 1 0 0 0 1.02679462
## [4,] 0 1 0 0 0 0.04809832
## [5,] 0 1 0 0 0 0.37433042
## [6,] 0 1 0 0 0 -0.93059797
## any_smoker smokeSH mean_cpss mean_epsd male gest_age_w days_to_peapod
## [1,] 0 1 3.3968005 -1.3157360 0 0.8044835 -0.2392302
## [2,] 0 0 0.1208193 -0.6918928 1 -2.7388783 0.1867962
## [3,] 0 0 0.1208193 -1.0038144 0 0.6971089 0.1867962
## [4,] 0 0 0.4484174 -1.3157360 0 -2.4167545 -0.2392302
## [5,] 0 0 -1.1895732 -1.3157360 1 -0.8061355 0.1867962
## [6,] 0 0 -0.5343769 -1.0038144 0 0.9118581 -0.2392302
summary(W.scaled)
## lat lon lat_lon_int latina_re
## Min. :-2.46715 Min. :-2.4830 Min. :-3.510301 Min. :0.0000
## 1st Qu.:-0.62450 1st Qu.:-0.5811 1st Qu.:-0.493286 1st Qu.:0.0000
## Median : 0.05945 Median : 0.1064 Median : 0.008488 Median :0.0000
## Mean : 0.00000 Mean : 0.0000 Mean : 0.000000 Mean :0.2628
## 3rd Qu.: 0.43089 3rd Qu.: 0.6643 3rd Qu.: 0.599123 3rd Qu.:1.0000
## Max. : 4.01365 Max. : 4.5155 Max. : 2.628224 Max. :1.0000
## black_re other_re ed_no_hs ed_hs
## Min. :0.0000 Min. :0.00000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.00000 Median :0.0000 Median :0.0000
## Mean :0.1654 Mean :0.06667 Mean :0.1538 Mean :0.1833
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00000 Max. :1.0000 Max. :1.0000
## ed_aa ed_4yr low_bmi ovwt_bmi
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.2256 Mean :0.2205 Mean :0.03077 Mean :0.2615
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## obese_bmi concep_spring concep_summer concep_fall
## Min. :0.0000 Min. :0.0000 Min. :0.00 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00 Median :0.0000
## Mean :0.1962 Mean :0.2436 Mean :0.25 Mean :0.2667
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.25 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00 Max. :1.0000
## concep_2010 concep_2011 concep_2012 concep_2013
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1692 Mean :0.2936 Mean :0.2808 Mean :0.2551
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## maternal_age any_smoker smokeSH mean_cpss
## Min. :-1.9093 Min. :0.00000 Min. :0.0000 Min. :-6.10355
## 1st Qu.:-0.9306 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:-0.53438
## Median : 0.0481 Median :0.00000 Median :0.0000 Median : 0.01162
## Mean : 0.0000 Mean :0.08718 Mean :0.2474 Mean : 0.00000
## 3rd Qu.: 0.7006 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.: 0.55762
## Max. : 2.6580 Max. :1.00000 Max. :1.0000 Max. : 3.39680
## mean_epsd male gest_age_w days_to_peapod
## Min. :-1.3157 Min. :0.0000 Min. :-5.20849 Min. :-0.6653
## 1st Qu.:-0.7959 1st Qu.:0.0000 1st Qu.:-0.48401 1st Qu.:-0.2392
## Median :-0.1720 Median :1.0000 Median : 0.05286 Median :-0.2392
## Mean : 0.0000 Mean :0.5064 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.5558 3rd Qu.:1.0000 3rd Qu.: 0.69711 3rd Qu.:-0.2392
## Max. : 3.9869 Max. :1.0000 Max. : 3.81097 Max. :10.4114
Variance and histograms for the scaled covariates
var(W.scaled)
## lat lon lat_lon_int latina_re
## lat 1.0000000000 -0.2294265015 -0.922594810 0.01488040464
## lon -0.2294265015 1.0000000000 0.587147326 0.00774099102
## lat_lon_int -0.9225948101 0.5871473257 1.000000000 -0.00928638293
## latina_re 0.0148804046 0.0077409910 -0.009286383 0.19399460189
## black_re -0.0076765642 0.0416993781 0.022926625 -0.04352226721
## other_re 0.0022244292 -0.0045513219 -0.003662305 -0.01754385965
## ed_no_hs -0.0002536098 0.0211421973 0.008600587 0.03781968994
## ed_hs -0.0092915161 0.0376437998 0.022660243 0.03262729996
## ed_aa -0.0072973858 0.0461167337 0.024355069 0.01250781739
## ed_4yr 0.0084748321 -0.0053108878 -0.009175293 -0.03620683980
## low_bmi -0.0031399188 0.0031935883 0.003878110 -0.00167868075
## ovwt_bmi 0.0176550362 0.0102854255 -0.010619251 0.02488397354
## obese_bmi 0.0151602612 0.0074254851 -0.009652703 0.02283499556
## concep_spring 0.0203171932 -0.0022492530 -0.017790516 -0.00633619697
## concep_summer -0.0229599220 -0.0001995618 0.019015261 -0.00417201540
## concep_fall 0.0095582094 0.0161897319 -0.001540859 0.01583226359
## concep_2010 0.0109529805 0.0028301792 -0.008007944 -0.00859089563
## concep_2011 -0.0226544797 0.0224924333 0.027745587 -0.01050821237
## concep_2012 0.0015394008 -0.0023870971 -0.002215499 0.01340475955
## concep_2013 0.0089319968 -0.0236248234 -0.016772917 0.00474803331
## maternal_age 0.0348578763 -0.1930103076 -0.105532928 -0.11130236864
## any_smoker -0.0069992076 0.0222429459 0.014635045 -0.00753760574
## smokeSH 0.0011347413 0.0442610839 0.016595995 -0.00349725157
## mean_cpss -0.0279187887 -0.0046586574 0.021381618 -0.04032749691
## mean_epsd -0.0458873302 0.0573784314 0.060923471 0.03908431534
## male 0.0224103855 -0.0245595335 -0.028364840 0.00152233304
## gest_age_w 0.0302744587 -0.0833518477 -0.058256588 -0.00772944439
## days_to_peapod 0.0166177524 -0.0037582676 -0.015297436 -0.00006310256
## black_re other_re ed_no_hs ed_hs
## lat -0.0076765642 0.0022244292 -0.0002536098 -0.0092915161
## lon 0.0416993781 -0.0045513219 0.0211421973 0.0376437998
## lat_lon_int 0.0229266248 -0.0036623054 0.0086005874 0.0226602429
## latina_re -0.0435222672 -0.0175438596 0.0378196899 0.0326273000
## black_re 0.1382097363 -0.0110397946 0.0143181594 0.0158536585
## other_re -0.0110397946 0.0623020967 -0.0025673941 0.0031664527
## ed_no_hs 0.0143181594 -0.0025673941 0.1303446233 -0.0282413350
## ed_hs 0.0158536585 0.0031664527 -0.0282413350 0.1499144202
## ed_aa 0.0178335144 0.0041934104 -0.0347585662 -0.0414206247
## ed_4yr -0.0172607880 -0.0031664527 -0.0339685988 -0.0404792469
## low_bmi 0.0026068925 -0.0007702182 -0.0034561074 -0.0005134788
## ovwt_bmi 0.0003357362 -0.0059050064 0.0046410586 -0.0069319641
## obese_bmi 0.0073121359 0.0023106547 0.0057272638 0.0268934531
## concep_spring -0.0005431026 0.0055626872 -0.0028636319 0.0014976466
## concep_summer -0.0067394095 0.0000000000 -0.0038510911 -0.0060975610
## concep_fall -0.0069319641 -0.0023962345 0.0102695764 0.0062473256
## concep_2010 0.0117705145 -0.0010269576 0.0008887133 0.0074454429
## concep_2011 0.0155672953 -0.0003423192 0.0112570356 -0.0063970903
## concep_2012 -0.0118346993 -0.0007702182 -0.0047398045 0.0062259307
## concep_2013 -0.0152908068 0.0022250749 -0.0072084527 -0.0070389388
## maternal_age -0.0914960717 -0.0135406562 -0.1473311448 -0.1061266380
## any_smoker 0.0150883776 -0.0006846384 0.0173792831 0.0045357296
## smokeSH 0.0321961094 0.0065896448 0.0324874099 0.0251818571
## mean_cpss -0.0362044396 0.0225734779 -0.0574356146 -0.0356451617
## mean_epsd 0.0160927464 0.0210839610 0.0715352956 0.0221439428
## male -0.0055544584 0.0021394951 -0.0151081268 0.0007488233
## gest_age_w -0.0459673981 -0.0051550835 -0.0121190054 -0.0148312028
## days_to_peapod 0.0353079864 0.0037188443 0.0068992133 0.0014765999
## ed_aa ed_4yr low_bmi ovwt_bmi
## lat -0.007297386 0.0084748321 -0.0031399188 0.0176550362
## lon 0.046116734 -0.0053108878 0.0031935883 0.0102854255
## lat_lon_int 0.024355069 -0.0091752931 0.0038781104 -0.0106192507
## latina_re 0.012507817 -0.0362068398 -0.0016786808 0.0248839735
## black_re 0.017833514 -0.0172607880 0.0026068925 0.0003357362
## other_re 0.004193410 -0.0031664527 -0.0007702182 -0.0059050064
## ed_no_hs -0.034758566 -0.0339685988 -0.0034561074 0.0046410586
## ed_hs -0.041420625 -0.0404792469 -0.0005134788 -0.0069319641
## ed_aa 0.174951450 -0.0498206116 0.0046015602 0.0179322603
## ed_4yr -0.049820612 0.1721075672 -0.0003752345 0.0013034462
## low_bmi 0.004601560 -0.0003752345 0.0298607682 -0.0080576676
## ovwt_bmi 0.017932260 0.0013034462 -0.0080576676 0.1933840229
## obese_bmi 0.012165498 -0.0137849314 -0.0060432507 -0.0513676311
## concep_spring 0.006583062 -0.0062868240 -0.0049372963 0.0068134689
## concep_summer -0.010269576 0.0089858793 0.0038510911 -0.0051347882
## concep_fall -0.010183997 0.0014548567 0.0033376123 0.0046213094
## concep_2010 0.002843883 0.0011454528 0.0024883974 -0.0032388664
## concep_2011 0.002988710 0.0057799282 0.0025081465 0.0065567295
## concep_2012 -0.005668016 -0.0067937198 -0.0047990520 -0.0054902735
## concep_2013 -0.001158619 0.0001514104 -0.0001579935 0.0025081465
## maternal_age -0.034152305 0.1077776102 -0.0091971230 0.0067327450
## any_smoker 0.008544814 -0.0153977815 0.0011652019 -0.0048582996
## smokeSH 0.021118462 -0.0353773740 0.0026463908 -0.0108818011
## mean_cpss 0.029189204 0.0275174804 0.0079977462 -0.0043164323
## mean_epsd 0.016391602 -0.0481925954 0.0107834260 0.0098080614
## male 0.001119121 0.0062868240 -0.0001974919 -0.0029623778
## gest_age_w -0.025824190 0.0330362179 -0.0033335217 -0.0159296533
## days_to_peapod 0.025249438 -0.0107106080 -0.0073703791 -0.0139751139
## obese_bmi concep_spring concep_summer concep_fall
## lat 0.015160261 0.0203171932 -0.0229599220 0.0095582094
## lon 0.007425485 -0.0022492530 -0.0001995618 0.0161897319
## lat_lon_int -0.009652703 -0.0177905156 0.0190152613 -0.0015408589
## latina_re 0.022834996 -0.0063361970 -0.0041720154 0.0158322636
## black_re 0.007312136 -0.0005431026 -0.0067394095 -0.0069319641
## other_re 0.002310655 0.0055626872 0.0000000000 -0.0023962345
## ed_no_hs 0.005727264 -0.0028636319 -0.0038510911 0.0102695764
## ed_hs 0.026893453 0.0014976466 -0.0060975610 0.0062473256
## ed_aa 0.012165498 0.0065830618 -0.0102695764 -0.0101839966
## ed_4yr -0.013784931 -0.0062868240 0.0089858793 0.0014548567
## low_bmi -0.006043251 -0.0049372963 0.0038510911 0.0033376123
## ovwt_bmi -0.051367631 0.0068134689 -0.0051347882 0.0046213094
## obese_bmi 0.157879925 -0.0029130048 -0.0054557125 -0.0048780488
## concep_spring -0.002913005 0.1844903064 -0.0609756098 -0.0650406504
## concep_summer -0.005455712 -0.0609756098 0.1877406932 -0.0667522465
## concep_fall -0.004878049 -0.0650406504 -0.0667522465 0.1958065896
## concep_2010 -0.004996544 -0.0233040387 0.0012836970 0.0267008986
## concep_2011 0.002671077 0.0041308713 -0.0003209243 -0.0129225503
## concep_2012 0.009040190 -0.0119976301 0.0016046213 0.0033376123
## concep_2013 -0.006462921 0.0314834930 -0.0022464698 -0.0167736414
## maternal_age -0.002069755 0.0029368513 0.0128775828 -0.0263135433
## any_smoker 0.003416609 -0.0007241368 0.0012836970 -0.0014548567
## smokeSH 0.011735953 -0.0051512458 -0.0093068036 -0.0005990586
## mean_cpss -0.017623185 0.0102636126 0.0090765847 -0.0058688239
## mean_epsd 0.021537334 -0.0093232881 -0.0185691459 0.0210706139
## male 0.000666535 -0.0028471742 -0.0073812580 -0.0017115961
## gest_age_w -0.018839063 -0.0120553886 -0.0012405281 0.0303791551
## days_to_peapod 0.003874497 0.0061840510 -0.0155863326 -0.0080939552
## concep_2010 concep_2011 concep_2012 concep_2013
## lat 0.0109529805 -0.0226544797 0.0015394008 0.0089319968
## lon 0.0028301792 0.0224924333 -0.0023870971 -0.0236248234
## lat_lon_int -0.0080079439 0.0277455872 -0.0022154991 -0.0167729167
## latina_re -0.0085908956 -0.0105082124 0.0134047596 0.0047480333
## black_re 0.0117705145 0.0155672953 -0.0118346993 -0.0152908068
## other_re -0.0010269576 -0.0003423192 -0.0007702182 0.0022250749
## ed_no_hs 0.0008887133 0.0112570356 -0.0047398045 -0.0072084527
## ed_hs 0.0074454429 -0.0063970903 0.0062259307 -0.0070389388
## ed_aa 0.0028438827 0.0029887100 -0.0056680162 -0.0011586189
## ed_4yr 0.0011454528 0.0057799282 -0.0067937198 0.0001514104
## low_bmi 0.0024883974 0.0025081465 -0.0047990520 -0.0001579935
## ovwt_bmi -0.0032388664 0.0065567295 -0.0054902735 0.0025081465
## obese_bmi -0.0049965439 0.0026710773 0.0090401896 -0.0064629209
## concep_spring -0.0233040387 0.0041308713 -0.0119976301 0.0314834930
## concep_summer 0.0012836970 -0.0003209243 0.0016046213 -0.0022464698
## concep_fall 0.0267008986 -0.0129225503 0.0033376123 -0.0167736414
## concep_2010 0.1407721931 -0.0497481979 -0.0475757875 -0.0432309667
## concep_2011 -0.0497481979 0.2076610381 -0.0825367829 -0.0749991771
## concep_2012 -0.0475757875 -0.0825367829 0.2021970969 -0.0717241039
## concep_2013 -0.0432309667 -0.0749991771 -0.0717241039 0.1902817550
## maternal_age -0.0328905868 -0.0432339945 0.0317389331 0.0462084289
## any_smoker 0.0031993680 0.0090319608 -0.0078206774 -0.0042987393
## smokeSH 0.0094203614 0.0145535038 -0.0182136862 -0.0067262434
## mean_cpss 0.0079265785 -0.0141064917 -0.0086484999 0.0104679503
## mean_epsd -0.0144672243 0.0406582459 -0.0297416911 0.0052396759
## male 0.0014811889 -0.0050936441 0.0014071295 0.0028554030
## gest_age_w -0.0066182705 -0.0045846526 0.0012150814 0.0089551286
## days_to_peapod -0.0279586414 -0.0014177042 -0.0328007113 0.0624841560
## maternal_age any_smoker smokeSH mean_cpss
## lat 0.034857876 -0.0069992076 0.0011347413 -0.027918789
## lon -0.193010308 0.0222429459 0.0442610839 -0.004658657
## lat_lon_int -0.105532928 0.0146350446 0.0165959949 0.021381618
## latina_re -0.111302369 -0.0075376057 -0.0034972516 -0.040327497
## black_re -0.091496072 0.0150883776 0.0321961094 -0.036204440
## other_re -0.013540656 -0.0006846384 0.0065896448 0.022573478
## ed_no_hs -0.147331145 0.0173792831 0.0324874099 -0.057435615
## ed_hs -0.106126638 0.0045357296 0.0251818571 -0.035645162
## ed_aa -0.034152305 0.0085448142 0.0211184622 0.029189204
## ed_4yr 0.107777610 -0.0153977815 -0.0353773740 0.027517480
## low_bmi -0.009197123 0.0011652019 0.0026463908 0.007997746
## ovwt_bmi 0.006732745 -0.0048582996 -0.0108818011 -0.004316432
## obese_bmi -0.002069755 0.0034166091 0.0117359534 -0.017623185
## concep_spring 0.002936851 -0.0007241368 -0.0051512458 0.010263613
## concep_summer 0.012877583 0.0012836970 -0.0093068036 0.009076585
## concep_fall -0.026313543 -0.0014548567 -0.0005990586 -0.005868824
## concep_2010 -0.032890587 0.0031993680 0.0094203614 0.007926578
## concep_2011 -0.043233995 0.0090319608 0.0145535038 -0.014106492
## concep_2012 0.031738933 -0.0078206774 -0.0182136862 -0.008648500
## concep_2013 0.046208429 -0.0042987393 -0.0067262434 0.010467950
## maternal_age 1.000000000 -0.0452178456 -0.1497337791 0.111663918
## any_smoker -0.045217846 0.0796813798 0.0490043119 0.012438902
## smokeSH -0.149733779 0.0490043119 0.1864504131 0.022013301
## mean_cpss 0.111663918 0.0124389018 0.0220133014 1.000000000
## mean_epsd -0.170707705 0.0453127030 0.1111391210 0.441020650
## male 0.026063884 0.0020078338 0.0016210790 -0.007214721
## gest_age_w 0.073088144 -0.0297069373 -0.0509973685 -0.007275391
## days_to_peapod -0.001591990 -0.0022885196 0.0107316422 -0.005995421
## mean_epsd male gest_age_w days_to_peapod
## lat -0.045887330 0.0224103855 0.030274459 0.01661775239
## lon 0.057378431 -0.0245595335 -0.083351848 -0.00375826760
## lat_lon_int 0.060923471 -0.0283648398 -0.058256588 -0.01529743598
## latina_re 0.039084315 0.0015223330 -0.007729444 -0.00006310256
## black_re 0.016092746 -0.0055544584 -0.045967398 0.03530798637
## other_re 0.021083961 0.0021394951 -0.005155083 0.00371884427
## ed_no_hs 0.071535296 -0.0151081268 -0.012119005 0.00689921335
## ed_hs 0.022143943 0.0007488233 -0.014831203 0.00147659993
## ed_aa 0.016391602 0.0011191205 -0.025824190 0.02524943813
## ed_4yr -0.048192595 0.0062868240 0.033036218 -0.01071060804
## low_bmi 0.010783426 -0.0001974919 -0.003333522 -0.00737037914
## ovwt_bmi 0.009808061 -0.0029623778 -0.015929653 -0.01397511387
## obese_bmi 0.021537334 0.0006665350 -0.018839063 0.00387449725
## concep_spring -0.009323288 -0.0028471742 -0.012055389 0.00618405099
## concep_summer -0.018569146 -0.0073812580 -0.001240528 -0.01558633260
## concep_fall 0.021070614 -0.0017115961 0.030379155 -0.00809395517
## concep_2010 -0.014467224 0.0014811889 -0.006618270 -0.02795864142
## concep_2011 0.040658246 -0.0050936441 -0.004584653 -0.00141770421
## concep_2012 -0.029741691 0.0014071295 0.001215081 -0.03280071127
## concep_2013 0.005239676 0.0028554030 0.008955129 0.06248415603
## maternal_age -0.170707705 0.0260638841 0.073088144 -0.00159199026
## any_smoker 0.045312703 0.0020078338 -0.029706937 -0.00228851955
## smokeSH 0.111139121 0.0016210790 -0.050997369 0.01073164223
## mean_cpss 0.441020650 -0.0072147212 -0.007275391 -0.00599542077
## mean_epsd 1.000000000 -0.0104804641 -0.086750438 0.01124930187
## male -0.010480464 0.2502797801 -0.039081937 0.03073094727
## gest_age_w -0.086750438 -0.0390819370 1.000000000 -0.13525838557
## days_to_peapod 0.011249302 0.0307309473 -0.135258386 1.00000000000
ggplot(pivot_longer(as.data.frame(W.scaled), lat:gest_age_w,
names_to = "exp", values_to = "value")) +
geom_histogram(aes(x = value)) +
facet_wrap(~ exp, scales = "free")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Y <- select(hs_data2, adiposity) %>%
as.matrix()
head(Y)
## adiposity
## [1,] 9.217429
## [2,] 7.736959
## [3,] 13.474442
## [4,] 10.058402
## [5,] 11.836774
## [6,] 15.544041
Distribution of adiposity and scaled adiposity
hist(Y, breaks = 20)
hist(scale(Y), breaks = 20)
Both adiposity (Y) and the exposures are scaled here
NOTE: Don’t use these plots as a way to estimate how many predictors might make the cut. This should be done a priori
df <- as.data.frame(cbind(scale(Y), X.scaled))
# par(mfrow=c(5,4))
sapply(2:length(df), function(x){
lm.x <- lm(adiposity ~ df[,x], data = df)
plot(df[,c(x, 1)],
xlab = paste0(colnames(df)[x], " beta: ",
round(summary(lm.x)$coef[2,1],4),
"; p = ",
round(summary(lm.x)$coef[2,4],4)))
abline(lm.x)
})
## [[1]]
## NULL
##
## [[2]]
## NULL
##
## [[3]]
## NULL
##
## [[4]]
## NULL
##
## [[5]]
## NULL
##
## [[6]]
## NULL
##
## [[7]]
## NULL
##
## [[8]]
## NULL
##
## [[9]]
## NULL
##
## [[10]]
## NULL
##
## [[11]]
## NULL
##
## [[12]]
## NULL
##
## [[13]]
## NULL
##
## [[14]]
## NULL
##
## [[15]]
## NULL
##
## [[16]]
## NULL
##
## [[17]]
## NULL
##
## [[18]]
## NULL
##
## [[19]]
## NULL
##
## [[20]]
## NULL
##
## [[21]]
## NULL
I.e., is there a relationship between our exposures and gestational age?
The DAG might look something like this:
exposures —> gestational age —> adiposity _________________________________^
Both gestational age and the exposures are scaled here. Gestational age measured in weeks from estimated date of conception to delivery
Since there were some (small) relationships between exposures and gestational age (based on simple linear regression models– namely the ozone and SES indicators), I’m going to omit this covariate for now.
df2 <- as.data.frame(cbind(W.scaled[,"gest_age_w"], X.scaled))
colnames(df2)[1] <- "gest_age_w"
# par(mfrow=c(5,4))
sapply(2:length(df2), function(x){
lm.x <- lm(gest_age_w ~ df2[,x], data = df2)
plot(df2[,c(x, 1)],
xlab = paste0(colnames(df2)[x], " beta: ",
round(summary(lm.x)$coef[2,1],4),
"; p = ",
round(summary(lm.x)$coef[2,4],4)))
abline(lm.x)
})
## [[1]]
## NULL
##
## [[2]]
## NULL
##
## [[3]]
## NULL
##
## [[4]]
## NULL
##
## [[5]]
## NULL
##
## [[6]]
## NULL
##
## [[7]]
## NULL
##
## [[8]]
## NULL
##
## [[9]]
## NULL
##
## [[10]]
## NULL
##
## [[11]]
## NULL
##
## [[12]]
## NULL
##
## [[13]]
## NULL
##
## [[14]]
## NULL
##
## [[15]]
## NULL
##
## [[16]]
## NULL
##
## [[17]]
## NULL
##
## [[18]]
## NULL
##
## [[19]]
## NULL
##
## [[20]]
## NULL
##
## [[21]]
## NULL
Dropping gest_age_w from the covariates
colnames(W.scaled)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "gest_age_w" "days_to_peapod"
W.scaled2 <- W.scaled[,-c(ncol(W.scaled)-1)]
colnames(W.scaled2)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "days_to_peapod"
To see if there might be something going on, Lauren suggested a ridge regression with a small penalty.
set.seed(123)
library(glmnet)
## Loading required package: Matrix
##
## Attaching package: 'Matrix'
## The following objects are masked from 'package:tidyr':
##
## expand, pack, unpack
## Loaded glmnet 4.0-2
lambda_seq <- 10^seq(4, -4, by = -.05)
#' Best lambda from CV
ridge_cv <- cv.glmnet(X, Y, alpha = 0, lambda = lambda_seq,
standardize = T, standardize.response = T)
plot(ridge_cv)
best_lambda <- ridge_cv$lambda.min
best_lambda
## [1] 31.62278
#' Fit the model using the best_lambda
ad_ridge <- glmnet(X, Y, alpha = 0, lambda = best_lambda,
standardize = T, standardize.response = T)
summary(ad_ridge)
## Length Class Mode
## a0 1 -none- numeric
## beta 21 dgCMatrix S4
## df 1 -none- numeric
## dim 2 -none- numeric
## lambda 1 -none- numeric
## dev.ratio 1 -none- numeric
## nulldev 1 -none- numeric
## npasses 1 -none- numeric
## jerr 1 -none- numeric
## offset 1 -none- logical
## call 7 -none- call
## nobs 1 -none- numeric
Ridge regression coefficients
coef(ad_ridge)
## 22 x 1 sparse Matrix of class "dgCMatrix"
## s0
## (Intercept) 9.62868020454909
## mean_pm -0.02639965648569
## mean_o3 -0.00149863384507
## mean_temp 0.00035436690634
## pct_tree_cover -0.00639632089744
## pct_impervious -0.00115374895744
## mean_aadt_intensity 0.00000005413306
## dist_m_tri 0.00000254982195
## dist_m_npl 0.00000201927869
## dist_m_waste_site 0.00001122409928
## dist_m_major_emit 0.00000316525795
## dist_m_cafo -0.00000138036863
## dist_m_mine_well -0.00000693864929
## cvd_rate_adj -0.00037383477626
## res_rate_adj -0.00077204501915
## violent_crime_rate -0.00212155361425
## property_crime_rate -0.00074961143159
## pct_less_hs -0.00020615684880
## pct_unemp -0.00414540443803
## pct_limited_eng 0.00144754271022
## pct_hh_pov -0.00182634711100
## pct_poc 0.00029616109913
Ridge regression predictions
ridge_pred <- predict(ad_ridge, newx = X)
plot(Y, ridge_pred)
actual <- Y
preds <- ridge_pred
rsq <- 1 - (sum((preds - actual) ^ 2))/(sum((actual - mean(actual)) ^ 2))
The R2 value for this model is 0.01. Based on these results, it doesn’t look like there’s much here.
Still, we wanted to try to fit the NPB model with these data.
I’m starting with the sets of priors used in the birth weight analysis. Note: I’m including far fewer iterations of the priors than in the previous version of the document.
set.seed(123)
priors.npb.1 <- list(alpha.pi = 1, beta.pi = 1, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 1)
fit.npb.1 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.1, interact = F)
npb.sum.1 <- summary(fit.npb.1)
npb.sum.1$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.00251899160 0.01678945 -0.03975440 0.0000000 0.060
## [2,] -0.00697160371 0.03431486 -0.09811891 0.0000000 0.092
## [3,] -0.00380585290 0.02717848 -0.05020675 0.0000000 0.074
## [4,] -0.00003156695 0.02579996 -0.02895671 0.0000000 0.060
## [5,] -0.00334740285 0.02130686 -0.04523678 0.0000000 0.072
## [6,] 0.00014552465 0.02280629 -0.02096066 0.0000000 0.050
## [7,] -0.00348068643 0.02742249 -0.05043653 0.0000000 0.068
## [8,] -0.00223689808 0.01510690 -0.03758662 0.0000000 0.062
## [9,] 0.00972022234 0.06317830 -0.01193044 0.1676507 0.070
## [10,] -0.00184770555 0.01893606 -0.04149589 0.0000000 0.072
## [11,] -0.00177345723 0.04496029 -0.04607937 0.0000000 0.086
## [12,] -0.00385506190 0.01966658 -0.06590866 0.0000000 0.072
## [13,] -0.00418350090 0.02432050 -0.05298671 0.0000000 0.072
## [14,] -0.00478567731 0.02835075 -0.08053355 0.0000000 0.082
## [15,] -0.00563577569 0.02816203 -0.08053355 0.0000000 0.078
## [16,] -0.00886650240 0.04640896 -0.11897728 0.0000000 0.096
## [17,] -0.00339000993 0.02288352 -0.03975440 0.0000000 0.060
## [18,] -0.00500625385 0.03089999 -0.06444760 0.0000000 0.078
## [19,] -0.00301121979 0.02423689 -0.04945271 0.0000000 0.070
## [20,] -0.00451592686 0.02868031 -0.05662754 0.0000000 0.064
## [21,] -0.00139528546 0.01676618 -0.02895671 0.0000000 0.050
plot(fit.npb.1$beta[,1], type = "l")
plot(fit.npb.1$beta[,2], type = "l")
plot(fit.npb.1$beta[,13], type = "l")
For now, leave a.phi1 and sig2inv.mu1 alone for now.
alpha.pi and beta.pi are responisble for the exclusion probability distribution. If we thing we want ~50% of our covariates, we need the mass of this distribution to be somewhere between 0.4 and 0.6. To do this, we set alpha.pi and beta.pi to the same value
plot(density(rbeta(10000, 2, 2)))
priors.npb.12 <- list(alpha.pi = 2, beta.pi = 2, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 1, sig2inv.mu1 = 1)
fit.npb.12 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.12, interact = F)
npb.sum.12 <- summary(fit.npb.12)
npb.sum.12$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.0059157857 0.03377064 -0.097474005 0.0004792181 0.100
## [2,] -0.0090463153 0.04653504 -0.125840618 0.0000000000 0.096
## [3,] -0.0084161455 0.05013707 -0.093931093 0.0000000000 0.106
## [4,] -0.0010198837 0.02505189 -0.054480140 0.0217012935 0.104
## [5,] -0.0048418847 0.02761684 -0.078374498 0.0000000000 0.114
## [6,] 0.0036931673 0.03794773 -0.025612089 0.0392846127 0.094
## [7,] -0.0042454533 0.02797184 -0.072847918 0.0051278635 0.104
## [8,] -0.0017935003 0.02515603 -0.065048094 0.0190562753 0.106
## [9,] 0.0149951440 0.07430073 -0.003587089 0.2867707922 0.106
## [10,] -0.0009999632 0.02067231 -0.049277540 0.0004792181 0.090
## [11,] -0.0101864863 0.09483126 -0.145606427 0.0000000000 0.126
## [12,] -0.0114217248 0.06188157 -0.199081888 0.0000000000 0.136
## [13,] -0.0090265096 0.04872197 -0.132097009 0.0000000000 0.118
## [14,] -0.0061123210 0.03001042 -0.086376809 0.0000000000 0.108
## [15,] -0.0040302357 0.02241392 -0.065048094 0.0000000000 0.094
## [16,] -0.0276631513 0.08308158 -0.340079717 0.0000000000 0.186
## [17,] -0.0076031044 0.04357811 -0.095937097 0.0000000000 0.104
## [18,] -0.0150402911 0.05389089 -0.216817306 0.0000000000 0.132
## [19,] -0.0025016035 0.02953072 -0.064428284 0.0000000000 0.104
## [20,] -0.0082003857 0.04223308 -0.107988449 0.0000000000 0.108
## [21,] -0.0047967090 0.03196737 -0.065560690 0.0000000000 0.110
plot(fit.npb.12$beta[,1], type = "l")
plot(fit.npb.12$beta[,2], type = "l")
plot(fit.npb.12$beta[,13], type = "l")
plot(density(rbeta(10000, 5, 5)))
priors.npb.13 <- list(alpha.pi = 5, beta.pi = 5, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 1, sig2inv.mu1 = 1)
fit.npb.13 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.13, interact = F)
npb.sum.13 <- summary(fit.npb.13)
npb.sum.13$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.013588720 0.04611916 -0.15037954 0.037021341 0.268
## [2,] -0.022858449 0.06363567 -0.19568711 0.030966082 0.328
## [3,] -0.022398483 0.05952143 -0.19333262 0.023371966 0.300
## [4,] -0.012316437 0.04241531 -0.13775235 0.054945953 0.294
## [5,] -0.013926848 0.04523430 -0.15122532 0.027201280 0.260
## [6,] 0.001723776 0.04522218 -0.07693582 0.117673348 0.210
## [7,] -0.017005195 0.05234701 -0.15205642 0.070711829 0.318
## [8,] -0.006933887 0.04615876 -0.13601461 0.080466077 0.220
## [9,] 0.009446499 0.06808085 -0.07788313 0.197738383 0.244
## [10,] -0.002334525 0.04383212 -0.09189281 0.096615301 0.196
## [11,] -0.020998685 0.07842284 -0.19413381 0.082415616 0.306
## [12,] -0.029195737 0.06329614 -0.20285059 0.027583540 0.376
## [13,] -0.024036571 0.06086846 -0.19859113 0.016850333 0.328
## [14,] -0.031272317 0.06841559 -0.22156602 0.022314462 0.358
## [15,] -0.018240412 0.04725588 -0.14530987 0.019420516 0.306
## [16,] -0.051474739 0.09408527 -0.35645755 0.010528957 0.442
## [17,] -0.018036891 0.05530325 -0.16237043 0.033679902 0.298
## [18,] -0.032465349 0.07385592 -0.23134535 0.007372234 0.338
## [19,] -0.008807566 0.04766809 -0.12392119 0.064478826 0.246
## [20,] -0.023856852 0.05857587 -0.17456581 0.017484307 0.334
## [21,] -0.011081707 0.04484714 -0.13407593 0.044814024 0.250
plot(fit.npb.13$beta[,1], type = "l")
plot(fit.npb.13$beta[,2], type = "l")
plot(fit.npb.13$beta[,13], type = "l")
plot(density(rbeta(10000, 8, 8)))
priors.npb.14 <- list(alpha.pi = 8, beta.pi = 8, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 1, sig2inv.mu1 = 1)
fit.npb.14 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.14, interact = F)
npb.sum.14 <- summary(fit.npb.14)
npb.sum.14$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.022061537 0.05066124 -0.16903610 0.021328953 0.354
## [2,] -0.035572741 0.08072661 -0.21655345 0.001175437 0.392
## [3,] -0.029063308 0.06705238 -0.18522465 0.025599131 0.410
## [4,] -0.016688688 0.04520342 -0.12922315 0.019569688 0.288
## [5,] -0.019509063 0.04647884 -0.13604458 0.011084979 0.340
## [6,] -0.005721694 0.03198458 -0.08768640 0.050736780 0.230
## [7,] -0.020214668 0.04548239 -0.15356206 0.009911258 0.322
## [8,] -0.010806016 0.03964471 -0.11704121 0.029248016 0.250
## [9,] 0.004633821 0.06718315 -0.09404629 0.204561960 0.250
## [10,] -0.009604285 0.03273550 -0.09972599 0.020629427 0.244
## [11,] -0.030995485 0.10296062 -0.24465104 0.028408061 0.348
## [12,] -0.036142851 0.07133508 -0.21246289 0.008649130 0.414
## [13,] -0.025958870 0.05273096 -0.15434401 0.018678411 0.378
## [14,] -0.031207791 0.05852112 -0.17103657 0.000000000 0.398
## [15,] -0.024205608 0.04438088 -0.12917096 0.000000000 0.372
## [16,] -0.061300783 0.09471326 -0.35912763 0.009911258 0.572
## [17,] -0.029055401 0.06341583 -0.19199711 0.000000000 0.360
## [18,] -0.044276687 0.08323885 -0.28271902 0.000000000 0.466
## [19,] -0.010766467 0.04328633 -0.10957762 0.012961829 0.258
## [20,] -0.028833342 0.06552176 -0.16440310 0.032408014 0.426
## [21,] -0.014307547 0.05244701 -0.13145177 0.032408014 0.332
plot(fit.npb.14$beta[,1], type = "l")
plot(fit.npb.14$beta[,2], type = "l")
plot(fit.npb.14$beta[,13], type = "l")
Set alpha.pi and beta.pi to 5, rather than 8, and try adjusting a.phi1 and sig2inv.mu1
priors.npb.23 <- list(alpha.pi = 5, beta.pi = 5, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 10, sig2inv.mu1 = 1)
fit.npb.23 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.23, interact = F)
npb.sum.23 <- summary(fit.npb.23)
npb.sum.23$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.019660880 0.05820927 -0.18105250 0.039970408 0.350
## [2,] -0.034407622 0.09020064 -0.24975240 0.027123403 0.358
## [3,] -0.023314205 0.08961590 -0.25125519 0.091702461 0.396
## [4,] -0.012069578 0.05024636 -0.13865664 0.068535705 0.298
## [5,] -0.016719850 0.04900707 -0.15113382 0.025023931 0.280
## [6,] 0.002090062 0.05927988 -0.09240788 0.144546324 0.226
## [7,] -0.016457220 0.05481142 -0.18551703 0.038588662 0.306
## [8,] -0.006310993 0.04581469 -0.11327386 0.087599079 0.282
## [9,] 0.020952898 0.09391984 -0.07714869 0.327656953 0.282
## [10,] -0.007427259 0.04372896 -0.10892163 0.085280776 0.262
## [11,] -0.028601270 0.09160631 -0.26113461 0.030443581 0.360
## [12,] -0.034856015 0.07817430 -0.25546804 0.045323348 0.418
## [13,] -0.029578632 0.06584658 -0.21727638 0.020161206 0.360
## [14,] -0.025649481 0.06680583 -0.21735549 0.043724461 0.362
## [15,] -0.015104051 0.05374696 -0.13996600 0.030443581 0.312
## [16,] -0.061796873 0.10230128 -0.34207021 0.007733966 0.494
## [17,] -0.024187697 0.06552762 -0.22722487 0.020151935 0.320
## [18,] -0.046991631 0.08782292 -0.31120390 0.017471708 0.436
## [19,] -0.001825107 0.06816709 -0.11245993 0.159510801 0.288
## [20,] -0.029272034 0.06400930 -0.21848942 0.029427512 0.392
## [21,] -0.010968743 0.04828661 -0.12980503 0.043451807 0.262
plot(fit.npb.23$beta[,1], type = "l")
plot(fit.npb.23$beta[,2], type = "l")
plot(fit.npb.23$beta[,13], type = "l")
priors.npb.24 <- list(alpha.pi = 5, beta.pi = 5, alpha.pi2 = 9, beta.pi2 = 1,
a.phi1 = 10, sig2inv.mu1 = 10)
fit.npb.24 <- npb(niter = 1000, nburn = 500, X = X.scaled, Y = Y, W = W.scaled2,
scaleY = TRUE,
priors = priors.npb.24, interact = F)
npb.sum.24 <- summary(fit.npb.24)
npb.sum.24$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.015441228 0.05365709 -0.18778448 0.053517848 0.288
## [2,] -0.028470447 0.08446267 -0.28886105 0.079914717 0.338
## [3,] -0.025337886 0.07808192 -0.20855982 0.094913039 0.362
## [4,] -0.009717591 0.04672317 -0.13688508 0.055852529 0.236
## [5,] -0.014361906 0.05980997 -0.16417365 0.070136787 0.284
## [6,] 0.006949586 0.05723496 -0.08069088 0.201369407 0.226
## [7,] -0.010557068 0.05331814 -0.14436623 0.094815375 0.294
## [8,] -0.006925859 0.05136525 -0.14295520 0.071612126 0.248
## [9,] 0.024503264 0.09474062 -0.07387488 0.320912825 0.258
## [10,] -0.001739784 0.04960022 -0.11195806 0.106455398 0.216
## [11,] -0.021143388 0.15092839 -0.29339219 0.150093071 0.382
## [12,] -0.036434479 0.08671000 -0.25716559 0.049885098 0.380
## [13,] -0.029240323 0.07398375 -0.25917362 0.027746224 0.344
## [14,] -0.031740847 0.07309448 -0.23224002 0.038268538 0.346
## [15,] -0.014061195 0.05869838 -0.16291040 0.111520930 0.304
## [16,] -0.080689978 0.11661307 -0.41096455 0.013294434 0.554
## [17,] -0.022079512 0.06342719 -0.19668896 0.043196527 0.312
## [18,] -0.053901519 0.10356736 -0.36311726 0.007025148 0.420
## [19,] -0.003006123 0.06095941 -0.11953655 0.076946265 0.248
## [20,] -0.033875702 0.09073772 -0.28665517 0.037627795 0.346
## [21,] -0.004821275 0.05669930 -0.13310703 0.118293021 0.280
plot(fit.npb.24$beta[,1], type = "l")
plot(fit.npb.24$beta[,2], type = "l")
plot(fit.npb.24$beta[,13], type = "l")
plot(fit.npb.24$beta[,15], type = "l")
As with the birth weight model, I’ve used the 24th set of priors and set scaleY = T in the NPB model below
The priors are as follows: r priors.npb.24
Note that this version of the model does not include gest_age_w. It does include an indicator variable for season of conception (ref = winter) and the lon/lat as covariates and the percentage of the census tract population that is not NHW as an exposure
priors.npb <- priors.npb.24
#' Exposures
colnames(X.scaled)
## [1] "mean_pm" "mean_o3" "mean_temp"
## [4] "pct_tree_cover" "pct_impervious" "mean_aadt_intensity"
## [7] "dist_m_tri" "dist_m_npl" "dist_m_waste_site"
## [10] "dist_m_major_emit" "dist_m_cafo" "dist_m_mine_well"
## [13] "cvd_rate_adj" "res_rate_adj" "violent_crime_rate"
## [16] "property_crime_rate" "pct_less_hs" "pct_unemp"
## [19] "pct_limited_eng" "pct_hh_pov" "pct_poc"
#' Covariates
colnames(W.scaled2)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "days_to_peapod"
# fit.npb <- npb(niter = 5000, nburn = 2500, X = X.scaled[,-c(3)], Y = Y, W = W.scaled2,
# scaleY = TRUE,
# priors = priors.npb, interact = TRUE, XWinteract = TRUE)
# save(fit.npb, file = here::here("Results", "NPB_Adiposity_v4.1.rdata"))
load(here::here("Results", "NPB_Adiposity_v4.1.rdata"))
npb.sum <- summary(fit.npb)
rownames(npb.sum$main.effects) <- colnames(X.scaled[,-c(3)])
npb.sum$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## mean_pm -0.010474845 0.05806874 -0.16399269 0.09724534 0.2764
## mean_o3 -0.033949010 0.09432840 -0.28579075 0.07311140 0.3588
## pct_tree_cover -0.009346531 0.05886109 -0.16062807 0.09357882 0.2632
## pct_impervious -0.014880529 0.05962135 -0.18533079 0.07258529 0.2744
## mean_aadt_intensity 0.011290602 0.06682281 -0.08592180 0.22515423 0.2484
## dist_m_tri -0.011534156 0.05975592 -0.17693313 0.10495805 0.2920
## dist_m_npl -0.002432396 0.05385284 -0.11687455 0.12756605 0.2504
## dist_m_waste_site 0.036118100 0.11404884 -0.07255974 0.41154804 0.3076
## dist_m_major_emit 0.003220441 0.06080674 -0.10592586 0.16131841 0.2420
## dist_m_cafo -0.018319667 0.11981956 -0.25346625 0.14292422 0.3296
## dist_m_mine_well -0.031663404 0.08083920 -0.26217059 0.06582362 0.3644
## cvd_rate_adj -0.025554316 0.06995234 -0.22843583 0.04040998 0.3272
## res_rate_adj -0.028767538 0.07078109 -0.24269889 0.02615036 0.3240
## violent_crime_rate -0.013232550 0.05730721 -0.16241997 0.07338247 0.2828
## property_crime_rate -0.072316252 0.12054928 -0.41474130 0.01445510 0.4804
## pct_less_hs -0.023573510 0.07524972 -0.24386951 0.06150607 0.3172
## pct_unemp -0.041639684 0.09036861 -0.31903345 0.02255897 0.3688
## pct_limited_eng 0.004783383 0.07139322 -0.10506007 0.21378057 0.2556
## pct_hh_pov -0.026256590 0.07209033 -0.23969670 0.02728443 0.3060
## pct_poc -0.004844897 0.06327005 -0.14293627 0.13767274 0.2588
rownames(npb.sum$covariates)[2:nrow(npb.sum$covariates)] <- colnames(W.scaled2)
npb.sum$covariates
## Posterior Mean SD 95% CI Lower 95% CI Upper
## <NA> 9.127935431 1.6677666 5.95798667 12.5342555
## lat 0.031977605 2.4410517 -4.94074344 4.7457325
## lon 0.235669894 1.1733445 -2.07440631 2.6381470
## lat_lon_int 0.008963015 2.9320047 -6.02234791 5.7766463
## latina_re -0.362339691 0.4002008 -1.11950574 0.4052584
## black_re -0.182765237 0.4412748 -1.03381038 0.6451597
## other_re -0.831500932 0.5779221 -1.97648630 0.2964177
## ed_no_hs 1.197403101 0.6499220 -0.09466340 2.4792122
## ed_hs 1.060905920 0.5668468 -0.07016721 2.1981973
## ed_aa 0.868996964 0.5098082 -0.14650376 1.8532053
## ed_4yr 0.152709061 0.4171839 -0.66819939 0.9519296
## low_bmi -0.436647700 0.7957353 -1.99452723 1.0911670
## ovwt_bmi 0.482555757 0.3354415 -0.19682896 1.1282273
## obese_bmi 1.278718523 0.3894703 0.52228455 2.0346581
## concep_spring 0.287729599 0.3995290 -0.48329179 1.0531830
## concep_summer 0.047447758 0.4368130 -0.81910262 0.8633053
## concep_fall -0.028994678 0.4379687 -0.94786015 0.7953698
## concep_2010 0.309248316 1.6426151 -3.02806988 3.3651487
## concep_2011 -0.223969599 1.6371429 -3.54869259 2.8528441
## concep_2012 -0.485681777 1.6312513 -3.77039887 2.6318421
## concep_2013 -0.194497210 1.6266547 -3.44644865 2.9839080
## maternal_age 0.739895938 0.1930571 0.35339477 1.1141247
## any_smoker -0.859131966 0.5289023 -1.89549602 0.1523035
## smokeSH -0.086310675 0.3734301 -0.82120421 0.6294554
## mean_cpss -0.038784716 0.1659860 -0.36101902 0.2801840
## mean_epsd -0.199755478 0.1657849 -0.52854381 0.1117160
## male -1.360027811 0.2710555 -1.88925706 -0.8241742
## days_to_peapod 0.832491618 0.1412240 0.56077789 1.1129369
Next, all of the interactions between exposures or between exposures and covariates
npb.sum$interactions
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] 0.0000751661711 0.0097209821 0 0 0.0020
## [2,] -0.0002005788630 0.0053181183 0 0 0.0020
## [3,] -0.0009736546023 0.0148194729 0 0 0.0056
## [4,] -0.0001366858739 0.0046123749 0 0 0.0020
## [5,] -0.0003487244809 0.0068381440 0 0 0.0028
## [6,] -0.0003818031305 0.0105623761 0 0 0.0024
## [7,] -0.0016712854795 0.0174415421 0 0 0.0112
## [8,] -0.0016522754155 0.0188527818 0 0 0.0100
## [9,] -0.0004154454531 0.0076703535 0 0 0.0040
## [10,] -0.0004777693515 0.0097924987 0 0 0.0032
## [11,] -0.0004619597843 0.0084150880 0 0 0.0032
## [12,] -0.0000893656268 0.0047993951 0 0 0.0024
## [13,] -0.0002095716927 0.0058911499 0 0 0.0024
## [14,] -0.0001837452631 0.0056096089 0 0 0.0024
## [15,] -0.0007198374311 0.0115484137 0 0 0.0044
## [16,] -0.0006202284124 0.0109699259 0 0 0.0040
## [17,] -0.0016713461178 0.0190179294 0 0 0.0092
## [18,] -0.0000556291708 0.0031681937 0 0 0.0016
## [19,] -0.0011153657671 0.0139346470 0 0 0.0076
## [20,] -0.0000277882137 0.0025423615 0 0 0.0020
## [21,] 0.0000050283688 0.0050812918 0 0 0.0012
## [22,] -0.0000205910561 0.0021767022 0 0 0.0016
## [23,] -0.0004864193355 0.0092428335 0 0 0.0048
## [24,] -0.0002280010578 0.0051817655 0 0 0.0020
## [25,] -0.0005492529542 0.0092032004 0 0 0.0048
## [26,] -0.0000428632044 0.0021431602 0 0 0.0004
## [27,] -0.0007758221035 0.0133243551 0 0 0.0048
## [28,] -0.0005808888965 0.0093148563 0 0 0.0048
## [29,] 0.0000935828564 0.0030264004 0 0 0.0020
## [30,] 0.0000216538378 0.0024962398 0 0 0.0020
## [31,] 0.0000205819623 0.0045398891 0 0 0.0016
## [32,] 0.0001612371806 0.0058900825 0 0 0.0020
## [33,] -0.0005744216191 0.0100806044 0 0 0.0036
## [34,] -0.0002234808194 0.0047085284 0 0 0.0036
## [35,] -0.0001105074658 0.0035494088 0 0 0.0012
## [36,] -0.0000676933179 0.0029969467 0 0 0.0016
## [37,] -0.0006507474995 0.0101481756 0 0 0.0048
## [38,] 0.0000000000000 0.0000000000 0 0 0.0000
## [39,] 0.0000941503249 0.0070910638 0 0 0.0016
## [40,] -0.0000298125854 0.0025779712 0 0 0.0020
## [41,] -0.0003359374637 0.0078172823 0 0 0.0024
## [42,] -0.0000808032198 0.0029041695 0 0 0.0008
## [43,] 0.0000861814881 0.0063388937 0 0 0.0024
## [44,] -0.0002636773428 0.0073892538 0 0 0.0020
## [45,] -0.0001020546378 0.0024281477 0 0 0.0024
## [46,] -0.0003747528128 0.0083467296 0 0 0.0036
## [47,] -0.0003045685988 0.0073179930 0 0 0.0028
## [48,] -0.0001505366505 0.0104927800 0 0 0.0028
## [49,] -0.0001200889901 0.0051301359 0 0 0.0016
## [50,] -0.0005102537461 0.0100230600 0 0 0.0032
## [51,] -0.0004332437989 0.0092964239 0 0 0.0024
## [52,] -0.0001458250813 0.0039324706 0 0 0.0016
## [53,] -0.0002747987574 0.0067628026 0 0 0.0024
## [54,] -0.0002954113512 0.0057792806 0 0 0.0032
## [55,] -0.0000725516743 0.0026815531 0 0 0.0008
## [56,] 0.0000169264274 0.0019779155 0 0 0.0016
## [57,] 0.0001305345087 0.0070166781 0 0 0.0016
## [58,] 0.0001601214089 0.0059331403 0 0 0.0020
## [59,] -0.0000484309243 0.0030747339 0 0 0.0012
## [60,] -0.0004995029758 0.0100749970 0 0 0.0028
## [61,] -0.0001397710723 0.0039405600 0 0 0.0016
## [62,] -0.0005631433530 0.0133591318 0 0 0.0040
## [63,] -0.0007996256009 0.0137450222 0 0 0.0048
## [64,] -0.0000300575165 0.0010003683 0 0 0.0012
## [65,] 0.0000000000000 0.0000000000 0 0 0.0000
## [66,] -0.0003243304752 0.0069584258 0 0 0.0028
## [67,] -0.0003026812637 0.0060186593 0 0 0.0028
## [68,] -0.0001000530466 0.0041931781 0 0 0.0032
## [69,] -0.0002001289925 0.0050504175 0 0 0.0028
## [70,] -0.0005639484509 0.0121373587 0 0 0.0028
## [71,] 0.0001037759208 0.0060392970 0 0 0.0024
## [72,] -0.0001677695224 0.0046879258 0 0 0.0024
## [73,] -0.0000673156074 0.0021033201 0 0 0.0012
## [74,] -0.0002837168937 0.0069050370 0 0 0.0024
## [75,] 0.0000907623925 0.0066024771 0 0 0.0020
## [76,] 0.0000529449425 0.0030043507 0 0 0.0008
## [77,] -0.0010191720200 0.0139619469 0 0 0.0060
## [78,] -0.0003084046769 0.0065656266 0 0 0.0032
## [79,] -0.0000987579867 0.0035998277 0 0 0.0016
## [80,] -0.0000606568524 0.0025699701 0 0 0.0008
## [81,] -0.0003957077732 0.0081596048 0 0 0.0032
## [82,] -0.0004060014114 0.0073807784 0 0 0.0036
## [83,] -0.0003029599471 0.0073510181 0 0 0.0040
## [84,] -0.0000924837699 0.0049309086 0 0 0.0016
## [85,] -0.0004872016473 0.0089190237 0 0 0.0052
## [86,] -0.0001069613316 0.0045031814 0 0 0.0016
## [87,] 0.0000028857398 0.0041322983 0 0 0.0020
## [88,] -0.0003319425603 0.0069981139 0 0 0.0040
## [89,] 0.0000511859717 0.0022079397 0 0 0.0008
## [90,] -0.0000851026343 0.0036052158 0 0 0.0008
## [91,] 0.0002093433561 0.0073691144 0 0 0.0036
## [92,] -0.0000418799360 0.0034014392 0 0 0.0020
## [93,] -0.0003720668971 0.0075541354 0 0 0.0040
## [94,] -0.0000955632905 0.0030490155 0 0 0.0012
## [95,] -0.0001262746757 0.0039071987 0 0 0.0016
## [96,] 0.0001466701540 0.0070801193 0 0 0.0012
## [97,] -0.0000536395266 0.0033549297 0 0 0.0012
## [98,] 0.0002635168904 0.0096970037 0 0 0.0032
## [99,] -0.0001139349156 0.0054544669 0 0 0.0016
## [100,] 0.0000498986888 0.0026699064 0 0 0.0016
## [101,] -0.0003240268991 0.0081177574 0 0 0.0040
## [102,] -0.0000546436030 0.0019334173 0 0 0.0008
## [103,] -0.0002607037385 0.0062257357 0 0 0.0028
## [104,] 0.0002027717289 0.0079107754 0 0 0.0032
## [105,] 0.0001914458798 0.0074062962 0 0 0.0020
## [106,] -0.0001398524223 0.0041377087 0 0 0.0012
## [107,] -0.0001102923373 0.0031709129 0 0 0.0016
## [108,] -0.0003452143057 0.0102498712 0 0 0.0024
## [109,] -0.0001531072587 0.0040030162 0 0 0.0020
## [110,] -0.0003130764811 0.0092524699 0 0 0.0016
## [111,] -0.0001800384167 0.0052766280 0 0 0.0020
## [112,] -0.0003223742082 0.0079391822 0 0 0.0024
## [113,] -0.0001421687959 0.0041819646 0 0 0.0012
## [114,] 0.0003638413089 0.0093730299 0 0 0.0016
## [115,] -0.0001744878048 0.0067134749 0 0 0.0020
## [116,] -0.0002064744935 0.0066785997 0 0 0.0028
## [117,] -0.0001499664939 0.0036420079 0 0 0.0028
## [118,] -0.0004246061606 0.0072163640 0 0 0.0048
## [119,] -0.0001806408383 0.0045642563 0 0 0.0032
## [120,] -0.0003158756561 0.0063944084 0 0 0.0032
## [121,] -0.0001789827315 0.0053398318 0 0 0.0024
## [122,] -0.0005157103872 0.0097127308 0 0 0.0052
## [123,] -0.0003006326854 0.0083086447 0 0 0.0024
## [124,] -0.0002579461877 0.0058814380 0 0 0.0024
## [125,] 0.0004200648050 0.0113102473 0 0 0.0032
## [126,] 0.0001276950637 0.0120096933 0 0 0.0040
## [127,] -0.0000690174496 0.0028426270 0 0 0.0024
## [128,] -0.0002236372263 0.0065508912 0 0 0.0024
## [129,] -0.0002071840026 0.0055858050 0 0 0.0020
## [130,] -0.0000116971060 0.0040317780 0 0 0.0016
## [131,] -0.0012517058751 0.0170697976 0 0 0.0084
## [132,] -0.0019072936159 0.0211683500 0 0 0.0112
## [133,] -0.0005054831540 0.0102625678 0 0 0.0032
## [134,] -0.0002061062083 0.0056494202 0 0 0.0016
## [135,] -0.0006021255642 0.0096296851 0 0 0.0048
## [136,] -0.0003824490149 0.0082821372 0 0 0.0036
## [137,] -0.0000354358860 0.0016072457 0 0 0.0008
## [138,] -0.0002157360687 0.0106312167 0 0 0.0032
## [139,] 0.0000099966057 0.0073421060 0 0 0.0016
## [140,] -0.0001226974246 0.0050659768 0 0 0.0012
## [141,] -0.0002626046751 0.0059638697 0 0 0.0028
## [142,] 0.0001057524433 0.0067480797 0 0 0.0012
## [143,] -0.0003574044163 0.0073629028 0 0 0.0032
## [144,] -0.0001812861793 0.0050857267 0 0 0.0016
## [145,] -0.0002338276145 0.0051277321 0 0 0.0036
## [146,] -0.0000408519211 0.0020425961 0 0 0.0004
## [147,] -0.0000511311478 0.0018075828 0 0 0.0008
## [148,] -0.0002118565939 0.0066348772 0 0 0.0012
## [149,] -0.0000506765349 0.0023956750 0 0 0.0008
## [150,] -0.0000227209774 0.0027544314 0 0 0.0016
## [151,] -0.0000082124367 0.0024058653 0 0 0.0028
## [152,] 0.0000159224292 0.0030496674 0 0 0.0016
## [153,] -0.0000264803704 0.0015567334 0 0 0.0008
## [154,] -0.0000378116076 0.0020365596 0 0 0.0024
## [155,] -0.0014300531739 0.0144341073 0 0 0.0124
## [156,] -0.0001882033814 0.0045091696 0 0 0.0020
## [157,] -0.0001645344626 0.0051147099 0 0 0.0012
## [158,] -0.0006781472124 0.0117522527 0 0 0.0040
## [159,] -0.0055279095032 0.0432175567 0 0 0.0212
## [160,] -0.0001168278872 0.0037910996 0 0 0.0012
## [161,] -0.0010040951319 0.0140106872 0 0 0.0064
## [162,] -0.0009484372392 0.0129589803 0 0 0.0076
## [163,] -0.0000364760509 0.0018141339 0 0 0.0012
## [164,] -0.0000283642029 0.0050076976 0 0 0.0024
## [165,] -0.0001579595138 0.0052186994 0 0 0.0012
## [166,] -0.0007238956012 0.0126764080 0 0 0.0044
## [167,] -0.0002674603393 0.0062380132 0 0 0.0036
## [168,] -0.0003145901499 0.0078539584 0 0 0.0024
## [169,] -0.0005937651225 0.0105368988 0 0 0.0044
## [170,] -0.0000094583730 0.0006629838 0 0 0.0008
## [171,] 0.0000647232773 0.0049078204 0 0 0.0020
## [172,] -0.0000028184191 0.0022345805 0 0 0.0008
## [173,] -0.0000115844362 0.0042967176 0 0 0.0012
## [174,] 0.0000188266149 0.0017366084 0 0 0.0008
## [175,] -0.0001382681933 0.0039680537 0 0 0.0016
## [176,] 0.0000957308901 0.0039725736 0 0 0.0012
## [177,] 0.0002056677385 0.0081780118 0 0 0.0020
## [178,] -0.0001264662756 0.0079513686 0 0 0.0036
## [179,] 0.0000000000000 0.0000000000 0 0 0.0000
## [180,] 0.0000545675325 0.0068734798 0 0 0.0020
## [181,] -0.0003238488978 0.0061188905 0 0 0.0036
## [182,] -0.0001378102478 0.0041570322 0 0 0.0012
## [183,] -0.0000815396707 0.0040769835 0 0 0.0004
## [184,] -0.0002310722681 0.0066484644 0 0 0.0024
## [185,] -0.0000428227080 0.0016992335 0 0 0.0016
## [186,] -0.0006053211220 0.0103328403 0 0 0.0048
## [187,] -0.0007093250417 0.0116413647 0 0 0.0044
## [188,] -0.0001236930019 0.0033347671 0 0 0.0016
## [189,] -0.0000261227146 0.0013061357 0 0 0.0004
## [190,] -0.0003680190176 0.0068832489 0 0 0.0044
## [191,] -0.0001388406572 0.0056931869 0 0 0.0028
## [192,] -0.0001608250851 0.0041039136 0 0 0.0016
## [193,] -0.0007257542169 0.0113756889 0 0 0.0056
## [194,] -0.0001125368287 0.0071616683 0 0 0.0028
## [195,] -0.0001148028412 0.0060025429 0 0 0.0036
## [196,] -0.0002810353801 0.0085344996 0 0 0.0036
## [197,] -0.0001751270166 0.0078503674 0 0 0.0020
## [198,] -0.0001735213528 0.0082121031 0 0 0.0020
## [199,] -0.0005499547777 0.0110736746 0 0 0.0032
## [200,] -0.0005207238105 0.0124029197 0 0 0.0040
## [201,] -0.0001170218219 0.0037076180 0 0 0.0016
## [202,] -0.0013627601745 0.0264890975 0 0 0.0052
## [203,] -0.0000568235199 0.0083337476 0 0 0.0024
## [204,] -0.0002481494126 0.0078173834 0 0 0.0032
## [205,] -0.0006682722609 0.0141030685 0 0 0.0048
## [206,] -0.0006901970702 0.0134428184 0 0 0.0044
## [207,] -0.0004745096605 0.0155932049 0 0 0.0032
## [208,] -0.0000847790687 0.0060486572 0 0 0.0012
## [209,] 0.0001544971816 0.0221166409 0 0 0.0028
## [210,] -0.0004169733006 0.0092547021 0 0 0.0036
## [211,] -0.0004996511864 0.0096419892 0 0 0.0036
## [212,] -0.0002057225914 0.0072024491 0 0 0.0028
## [213,] -0.0002426041357 0.0063110295 0 0 0.0024
## [214,] -0.0001287991305 0.0041108476 0 0 0.0020
## [215,] -0.0000485306715 0.0035450568 0 0 0.0016
## [216,] -0.0003467841483 0.0074728476 0 0 0.0024
## [217,] -0.0002548240529 0.0064973964 0 0 0.0020
## [218,] -0.0000228785333 0.0050676840 0 0 0.0016
## [219,] -0.0016163697211 0.0198059284 0 0 0.0080
## [220,] -0.0025687016084 0.0247410499 0 0 0.0144
## [221,] -0.0003423254932 0.0082575623 0 0 0.0032
## [222,] -0.0003308865171 0.0135397766 0 0 0.0044
## [223,] -0.0003745298887 0.0076732276 0 0 0.0032
## [224,] -0.0006419653464 0.0112783588 0 0 0.0068
## [225,] -0.0004070900378 0.0071979049 0 0 0.0036
## [226,] -0.0008509472949 0.0170261287 0 0 0.0044
## [227,] -0.0002550595151 0.0090477893 0 0 0.0028
## [228,] -0.0003602419471 0.0079081117 0 0 0.0024
## [229,] 0.0007335752432 0.0232858986 0 0 0.0028
## [230,] -0.0014812480333 0.0256283951 0 0 0.0076
## [231,] -0.0069925334184 0.0838365454 0 0 0.0112
## [232,] -0.0009750167832 0.0330173534 0 0 0.0036
## [233,] 0.0000239476601 0.0121241643 0 0 0.0052
## [234,] -0.0025861676000 0.0422076943 0 0 0.0068
## [235,] -0.0004506425698 0.0071452972 0 0 0.0052
## [236,] 0.0000307725611 0.0072164512 0 0 0.0016
## [237,] -0.0002636815601 0.0067783258 0 0 0.0020
## [238,] 0.0000041182899 0.0031257446 0 0 0.0008
## [239,] -0.0005993258348 0.0157463204 0 0 0.0036
## [240,] -0.0013364390579 0.0241499009 0 0 0.0052
## [241,] -0.0000499479692 0.0024973985 0 0 0.0004
## [242,] -0.0002023939755 0.0064156396 0 0 0.0020
## [243,] -0.0006226554071 0.0139607229 0 0 0.0040
## [244,] -0.0005900413855 0.0100360918 0 0 0.0044
## [245,] -0.0002110645749 0.0069665585 0 0 0.0024
## [246,] -0.0001101510375 0.0032683674 0 0 0.0012
## [247,] -0.0001554367329 0.0042371398 0 0 0.0016
## [248,] -0.0003968080406 0.0137394148 0 0 0.0032
## [249,] -0.0000165835102 0.0061526346 0 0 0.0024
## [250,] 0.0006045280034 0.0408870317 0 0 0.0040
## [251,] -0.0003404361898 0.0086897260 0 0 0.0032
## [252,] -0.0007598750678 0.0185165117 0 0 0.0032
## [253,] -0.0000286027514 0.0052893989 0 0 0.0036
## [254,] -0.0003443454414 0.0083923472 0 0 0.0028
## [255,] -0.0006409847845 0.0112197305 0 0 0.0044
## [256,] -0.0001903375220 0.0094373033 0 0 0.0048
## [257,] -0.0010942670322 0.0252251752 0 0 0.0048
## [258,] 0.0003859964748 0.0147098978 0 0 0.0016
## [259,] -0.0003058548320 0.0190917372 0 0 0.0060
## [260,] -0.0001054352106 0.0046511062 0 0 0.0016
## [261,] -0.0000452027083 0.0022601354 0 0 0.0004
## [262,] -0.0000962058313 0.0034893509 0 0 0.0008
## [263,] -0.0013576962088 0.0212670478 0 0 0.0064
## [264,] 0.0002979350233 0.0188742177 0 0 0.0024
## [265,] -0.0000326221516 0.0019529944 0 0 0.0016
## [266,] -0.0004880171714 0.0147210611 0 0 0.0024
## [267,] 0.0001010774921 0.0076816467 0 0 0.0040
## [268,] -0.0003432472654 0.0068730699 0 0 0.0032
## [269,] -0.0002910940925 0.0074098116 0 0 0.0020
## [270,] -0.0002814248222 0.0085884485 0 0 0.0020
## [271,] -0.0001375622917 0.0060080278 0 0 0.0024
## [272,] -0.0002498921519 0.0052493860 0 0 0.0028
## [273,] -0.0002672923421 0.0077295791 0 0 0.0020
## [274,] -0.0001318261565 0.0052906447 0 0 0.0020
## [275,] -0.0000593931748 0.0076815837 0 0 0.0016
## [276,] -0.0003070526119 0.0077797620 0 0 0.0032
## [277,] -0.0004305563973 0.0085580987 0 0 0.0040
## [278,] -0.0002571498155 0.0068521041 0 0 0.0016
## [279,] -0.0001848541009 0.0046309591 0 0 0.0028
## [280,] -0.0004308593891 0.0107325892 0 0 0.0040
## [281,] 0.0001168431333 0.0178039484 0 0 0.0036
## [282,] -0.0004451237028 0.0130926364 0 0 0.0028
## [283,] 0.0001079462296 0.0114153625 0 0 0.0032
## [284,] -0.0001431001128 0.0071286591 0 0 0.0032
## [285,] -0.0000447644279 0.0084970618 0 0 0.0048
## [286,] -0.0003573171678 0.0071275965 0 0 0.0032
## [287,] -0.0000385239907 0.0075973172 0 0 0.0024
## [288,] -0.0002146871772 0.0053981568 0 0 0.0020
## [289,] -0.0000496814342 0.0018581539 0 0 0.0012
## [290,] -0.0002405766490 0.0060848412 0 0 0.0028
## [291,] -0.0002178654702 0.0082063406 0 0 0.0012
## [292,] -0.0007250924962 0.0113585190 0 0 0.0044
## [293,] -0.0005927171006 0.0221920022 0 0 0.0020
## [294,] -0.0004226246794 0.0109146784 0 0 0.0056
## [295,] -0.0006423922724 0.0130145060 0 0 0.0056
## [296,] -0.0002611764427 0.0071156979 0 0 0.0024
## [297,] -0.0018865643422 0.0241634061 0 0 0.0088
## [298,] -0.0000478002851 0.0057231838 0 0 0.0028
## [299,] -0.0004222734525 0.0104107494 0 0 0.0024
## [300,] -0.0009288980322 0.0140406757 0 0 0.0068
## [301,] -0.0003058029421 0.0073365807 0 0 0.0032
## [302,] -0.0001866287786 0.0049600417 0 0 0.0020
## [303,] -0.0003834679125 0.0124989434 0 0 0.0028
## [304,] -0.0001906133040 0.0117677951 0 0 0.0024
## [305,] -0.0000019353721 0.0066542797 0 0 0.0024
## [306,] -0.0003396702295 0.0086073611 0 0 0.0024
## [307,] -0.0003528402430 0.0077496232 0 0 0.0028
## [308,] 0.0003967768585 0.0239380439 0 0 0.0040
## [309,] -0.0002141446113 0.0063302339 0 0 0.0012
## [310,] -0.0002089881337 0.0053858157 0 0 0.0020
## [311,] -0.0005525402247 0.0156678215 0 0 0.0028
## [312,] 0.0001331407757 0.0049961341 0 0 0.0020
## [313,] -0.0002391931374 0.0077854463 0 0 0.0016
## [314,] -0.0001953764455 0.0044639893 0 0 0.0032
## [315,] -0.0000613256049 0.0078538082 0 0 0.0020
## [316,] 0.0001431309642 0.0080041990 0 0 0.0016
## [317,] 0.0002917078697 0.0116544065 0 0 0.0028
## [318,] -0.0004290656696 0.0081053367 0 0 0.0044
## [319,] -0.0004599716799 0.0080955776 0 0 0.0040
## [320,] -0.0005056837910 0.0094937975 0 0 0.0036
## [321,] -0.0007567813276 0.0130609600 0 0 0.0048
## [322,] -0.0000033306803 0.0027799339 0 0 0.0012
## [323,] -0.0000686204655 0.0030535397 0 0 0.0020
## [324,] -0.0002480443648 0.0064689586 0 0 0.0024
## [325,] -0.0002779404954 0.0073339607 0 0 0.0024
## [326,] -0.0002850097478 0.0057802368 0 0 0.0028
## [327,] -0.0000031254058 0.0001562703 0 0 0.0004
## [328,] -0.0000454468360 0.0024156566 0 0 0.0016
## [329,] -0.0006038050755 0.0121503624 0 0 0.0032
## [330,] -0.0001602275856 0.0118881449 0 0 0.0024
## [331,] 0.0003573676364 0.0336911186 0 0 0.0036
## [332,] 0.0003874902091 0.0220633844 0 0 0.0036
## [333,] -0.0005440854767 0.0111187001 0 0 0.0028
## [334,] -0.0004574756402 0.0093713442 0 0 0.0028
## [335,] -0.0004071524760 0.0079084256 0 0 0.0036
## [336,] -0.0004295929805 0.0161420474 0 0 0.0056
## [337,] -0.0003077644117 0.0079104881 0 0 0.0036
## [338,] -0.0003459735989 0.0075811205 0 0 0.0024
## [339,] -0.0004707188064 0.0099161584 0 0 0.0032
## [340,] -0.0004731829534 0.0089468240 0 0 0.0048
## [341,] -0.0001474418369 0.0038858226 0 0 0.0020
## [342,] -0.0000694898722 0.0067990395 0 0 0.0052
## [343,] -0.0006387653573 0.0132024832 0 0 0.0036
## [344,] -0.0003489349505 0.0099483494 0 0 0.0028
## [345,] 0.0005353459217 0.0206255791 0 0 0.0048
## [346,] -0.0001784389040 0.0056493887 0 0 0.0016
## [347,] -0.0004085866430 0.0084684564 0 0 0.0032
## [348,] -0.0003217241778 0.0086413956 0 0 0.0024
## [349,] -0.0002351468738 0.0048851910 0 0 0.0028
## [350,] -0.0001913616378 0.0052551018 0 0 0.0020
## [351,] 0.0000001990147 0.0037431944 0 0 0.0008
## [352,] -0.0000114985148 0.0048940384 0 0 0.0016
## [353,] -0.0003904918990 0.0089110266 0 0 0.0024
## [354,] -0.0003265122864 0.0078518227 0 0 0.0028
## [355,] -0.0001336346624 0.0054205069 0 0 0.0024
## [356,] -0.0007732953670 0.0128195961 0 0 0.0052
## [357,] 0.0003800048953 0.0220052384 0 0 0.0044
## [358,] -0.0001670521759 0.0064107633 0 0 0.0020
## [359,] -0.0002012375028 0.0119431219 0 0 0.0032
## [360,] -0.0001933084679 0.0060699265 0 0 0.0012
## [361,] -0.0004401857850 0.0095950025 0 0 0.0036
## [362,] -0.0005770967199 0.0114307615 0 0 0.0036
## [363,] -0.0013988805177 0.0348625354 0 0 0.0056
## [364,] -0.0000947394756 0.0060078604 0 0 0.0032
## [365,] -0.0002312124620 0.0061140967 0 0 0.0028
## [366,] -0.0002708699885 0.0062588394 0 0 0.0020
## [367,] -0.0002343194102 0.0054684020 0 0 0.0020
## [368,] -0.0004621110113 0.0103172630 0 0 0.0032
## [369,] -0.0002048766003 0.0053918666 0 0 0.0020
## [370,] -0.0003708990674 0.0079255540 0 0 0.0028
## [371,] -0.0002465349961 0.0063016010 0 0 0.0036
## [372,] -0.0001490083039 0.0047849939 0 0 0.0012
## [373,] -0.0001948356324 0.0054371307 0 0 0.0020
## [374,] -0.0001370279763 0.0060231035 0 0 0.0024
## [375,] -0.0002214722720 0.0067833411 0 0 0.0028
## [376,] -0.0001424070417 0.0045994199 0 0 0.0024
## [377,] -0.0001434686747 0.0048425961 0 0 0.0016
## [378,] -0.0003050949808 0.0078078178 0 0 0.0028
## [379,] -0.0003235403378 0.0068299143 0 0 0.0028
## [380,] -0.0025231548846 0.0256023263 0 0 0.0124
## [381,] -0.0005095480944 0.0092901919 0 0 0.0048
## [382,] 0.0002453771891 0.0065973515 0 0 0.0020
## [383,] -0.0002045575143 0.0074459915 0 0 0.0008
## [384,] 0.0000561188051 0.0060387407 0 0 0.0028
## [385,] 0.0033548447303 0.0705233407 0 0 0.0044
## [386,] -0.0000903749055 0.0028187546 0 0 0.0012
## [387,] -0.0001487835118 0.0062997007 0 0 0.0024
## [388,] 0.0002508915241 0.0133816520 0 0 0.0028
## [389,] 0.0000042434050 0.0047038454 0 0 0.0020
## [390,] -0.0006523812679 0.0151738700 0 0 0.0048
## [391,] -0.0000262362714 0.0091184597 0 0 0.0020
## [392,] -0.0003424567778 0.0100340863 0 0 0.0036
## [393,] -0.0001928472976 0.0065652660 0 0 0.0032
## [394,] 0.0001051131356 0.0072072629 0 0 0.0024
## [395,] -0.0000233878164 0.0015866788 0 0 0.0012
## [396,] -0.0002417590909 0.0061810894 0 0 0.0020
## [397,] 0.0008277790111 0.0264870998 0 0 0.0024
## [398,] -0.0004509331286 0.0093500218 0 0 0.0044
## [399,] 0.0000522273387 0.0133932962 0 0 0.0032
## [400,] -0.0001644965503 0.0065243514 0 0 0.0024
## [401,] 0.0000588294480 0.0219371028 0 0 0.0036
## [402,] -0.0003351184933 0.0074176608 0 0 0.0024
## [403,] 0.0001014199289 0.0048339570 0 0 0.0020
## [404,] -0.0002107725941 0.0064848251 0 0 0.0028
## [405,] -0.0003252646847 0.0068018284 0 0 0.0040
## [406,] -0.0000076196386 0.0011413862 0 0 0.0012
## [407,] -0.0013441963148 0.0150630735 0 0 0.0088
## [408,] -0.0006541512791 0.0108234341 0 0 0.0044
## [409,] 0.0000856702461 0.0048203632 0 0 0.0024
## [410,] -0.0001908953821 0.0064745969 0 0 0.0040
## [411,] 0.0002231188174 0.0109396843 0 0 0.0032
## [412,] -0.0003271333714 0.0064153432 0 0 0.0040
## [413,] -0.0002373285340 0.0103479171 0 0 0.0036
## [414,] -0.0005218044869 0.0174716172 0 0 0.0056
## [415,] -0.0000409573142 0.0084813925 0 0 0.0016
## [416,] -0.0001464235282 0.0052004111 0 0 0.0008
## [417,] -0.0003733203127 0.0099775412 0 0 0.0044
## [418,] 0.0004415618717 0.0175999933 0 0 0.0048
## [419,] -0.0002325578078 0.0052832968 0 0 0.0020
## [420,] -0.0001386727637 0.0055817872 0 0 0.0024
## [421,] -0.0004447531870 0.0114210815 0 0 0.0048
## [422,] -0.0005079637047 0.0108345643 0 0 0.0032
## [423,] -0.0002264185315 0.0053783885 0 0 0.0032
## [424,] -0.0000283357499 0.0051723968 0 0 0.0032
## [425,] -0.0003187741800 0.0074050274 0 0 0.0036
## [426,] 0.0001118703452 0.0076200978 0 0 0.0012
## [427,] 0.0000358793225 0.0071809147 0 0 0.0028
## [428,] -0.0000568986649 0.0088897299 0 0 0.0036
## [429,] -0.0001634146558 0.0038951918 0 0 0.0020
## [430,] -0.0000891436246 0.0032163310 0 0 0.0020
## [431,] -0.0001287276769 0.0062713960 0 0 0.0012
## [432,] 0.0000862310517 0.0035743766 0 0 0.0028
## [433,] -0.0002047701018 0.0056197922 0 0 0.0020
## [434,] 0.0000191871114 0.0022835677 0 0 0.0016
## [435,] -0.0001278116908 0.0038191429 0 0 0.0012
## [436,] -0.0004725178323 0.0098953291 0 0 0.0064
## [437,] -0.0000722575338 0.0111492737 0 0 0.0028
## [438,] -0.0000327724598 0.0020430107 0 0 0.0012
## [439,] 0.0001266296234 0.0151772730 0 0 0.0020
## [440,] 0.0011184739634 0.0431067943 0 0 0.0020
## [441,] -0.0005276780434 0.0106623596 0 0 0.0028
## [442,] -0.0002188261840 0.0070433195 0 0 0.0016
## [443,] -0.0001789026506 0.0061397253 0 0 0.0016
## [444,] -0.0005531511288 0.0324732677 0 0 0.0036
## [445,] -0.0000638477486 0.0055926879 0 0 0.0032
## [446,] -0.0003928826205 0.0083179869 0 0 0.0032
## [447,] -0.0002018062801 0.0094592048 0 0 0.0052
## [448,] -0.0002931417794 0.0059768214 0 0 0.0044
## [449,] -0.0000793306522 0.0062787353 0 0 0.0024
## [450,] -0.0001585218816 0.0080680893 0 0 0.0024
## [451,] -0.0001016399128 0.0102419494 0 0 0.0028
## [452,] -0.0008653812626 0.0156803006 0 0 0.0064
## [453,] -0.0000766289510 0.0095509212 0 0 0.0032
## [454,] -0.0003332360156 0.0068401071 0 0 0.0028
## [455,] 0.0002505551035 0.0148406196 0 0 0.0032
## [456,] 0.0000125199263 0.0119239869 0 0 0.0040
## [457,] -0.0003353127373 0.0077249209 0 0 0.0028
## [458,] -0.0001543634294 0.0052032104 0 0 0.0020
## [459,] -0.0004161903516 0.0084952616 0 0 0.0032
## [460,] -0.0001533369508 0.0059785140 0 0 0.0016
## [461,] -0.0002750589766 0.0066235790 0 0 0.0020
## [462,] -0.0001493970898 0.0047225109 0 0 0.0024
## [463,] -0.0001462399864 0.0046452197 0 0 0.0028
## [464,] -0.0001421169815 0.0076963149 0 0 0.0016
## [465,] -0.0003615375773 0.0075650680 0 0 0.0036
## [466,] -0.0003681778008 0.0125479961 0 0 0.0032
## [467,] -0.0004606970858 0.0142210469 0 0 0.0032
## [468,] -0.0007205710824 0.0141344435 0 0 0.0044
## [469,] -0.0000318269792 0.0013812378 0 0 0.0012
## [470,] -0.0002397112447 0.0056212128 0 0 0.0032
## [471,] -0.0001541085110 0.0055088257 0 0 0.0020
## [472,] -0.0004526815447 0.0122429239 0 0 0.0040
## [473,] -0.0005384340237 0.0093224060 0 0 0.0044
## [474,] -0.0002445794144 0.0060595286 0 0 0.0024
## [475,] -0.0009553638304 0.0168853899 0 0 0.0052
## [476,] 0.0000760275112 0.0065812333 0 0 0.0028
## [477,] -0.0002311791861 0.0064654192 0 0 0.0020
## [478,] -0.0001573891427 0.0044260550 0 0 0.0016
## [479,] -0.0015326729490 0.0212499553 0 0 0.0068
## [480,] -0.0000973813172 0.0037762818 0 0 0.0008
## [481,] -0.0002593710382 0.0062661793 0 0 0.0020
## [482,] -0.0002491105393 0.0072909881 0 0 0.0028
## [483,] -0.0003037467373 0.0065355314 0 0 0.0028
## [484,] -0.0001491252554 0.0049387312 0 0 0.0016
## [485,] 0.0000429027026 0.0037691706 0 0 0.0016
## [486,] -0.0002156622377 0.0094961507 0 0 0.0032
## [487,] -0.0002546418799 0.0061447747 0 0 0.0020
## [488,] -0.0002423088548 0.0050905397 0 0 0.0028
## [489,] -0.0005169058603 0.0097207401 0 0 0.0044
## [490,] -0.0001936680954 0.0049827522 0 0 0.0028
## [491,] -0.0006274750985 0.0104753671 0 0 0.0044
## [492,] -0.0003823083184 0.0073614872 0 0 0.0032
## [493,] -0.0029212618799 0.0535074895 0 0 0.0084
## [494,] -0.0000591528252 0.0029576413 0 0 0.0004
## [495,] -0.0004228779946 0.0085112051 0 0 0.0044
## [496,] -0.0000240759206 0.0053788160 0 0 0.0028
## [497,] -0.0002916896612 0.0085857416 0 0 0.0028
## [498,] -0.0004333908022 0.0100168792 0 0 0.0052
## [499,] 0.0001999355941 0.0120698419 0 0 0.0024
## [500,] -0.0005118718854 0.0093733649 0 0 0.0056
## [501,] -0.0006005119012 0.0134788530 0 0 0.0036
## [502,] -0.0004815499937 0.0093370155 0 0 0.0036
## [503,] -0.0004539452814 0.0090916965 0 0 0.0036
## [504,] -0.0009244514096 0.0142051813 0 0 0.0064
## [505,] -0.0003960822184 0.0079459124 0 0 0.0044
## [506,] 0.0000309363810 0.0069485316 0 0 0.0016
## [507,] -0.0002961878191 0.0070078014 0 0 0.0024
## [508,] -0.0001860789290 0.0052508247 0 0 0.0032
## [509,] -0.0002335790938 0.0046706582 0 0 0.0028
## [510,] -0.0007458897215 0.0118997348 0 0 0.0048
## [511,] -0.0002964392474 0.0068394860 0 0 0.0028
## [512,] -0.0000326079342 0.0013068576 0 0 0.0012
## [513,] -0.0004134917786 0.0089180836 0 0 0.0024
## [514,] -0.0022168078689 0.0275792692 0 0 0.0096
## [515,] -0.0001732648223 0.0085361709 0 0 0.0028
## [516,] -0.0005684537642 0.0090767831 0 0 0.0052
## [517,] -0.0004441443323 0.0084767440 0 0 0.0036
## [518,] -0.0003708018616 0.0094045321 0 0 0.0036
## [519,] 0.0000367326159 0.0095288445 0 0 0.0028
## [520,] -0.0019026448600 0.0474763636 0 0 0.0080
## [521,] -0.0003128234977 0.0072104252 0 0 0.0020
## [522,] -0.0004071825712 0.0134397480 0 0 0.0032
## [523,] -0.0001486793807 0.0038486009 0 0 0.0028
## [524,] -0.0009478386521 0.0137648088 0 0 0.0056
## [525,] -0.0009808472975 0.0308783177 0 0 0.0028
## [526,] 0.0010123029825 0.0255818002 0 0 0.0040
## [527,] -0.0002512089003 0.0065764079 0 0 0.0020
## [528,] -0.0006154968446 0.0128070518 0 0 0.0052
## [529,] -0.0003349490025 0.0096938152 0 0 0.0036
## [530,] -0.0005790830477 0.0101169415 0 0 0.0044
## [531,] -0.0007193672671 0.0124480572 0 0 0.0052
## [532,] -0.0001539425860 0.0036590266 0 0 0.0024
## [533,] -0.0002891631306 0.0070819567 0 0 0.0020
## [534,] -0.0003406445763 0.0081000750 0 0 0.0036
## [535,] -0.0004515787267 0.0101748858 0 0 0.0028
## [536,] -0.0004684568134 0.0146963503 0 0 0.0024
## [537,] -0.0006751443410 0.0153209876 0 0 0.0036
## [538,] -0.0000725942594 0.0029989094 0 0 0.0012
## [539,] -0.0001943843657 0.0057334844 0 0 0.0012
## [540,] -0.0005364819479 0.0095565098 0 0 0.0044
## [541,] -0.0025672920253 0.0308027599 0 0 0.0108
## [542,] -0.0000810910400 0.0054726278 0 0 0.0012
## [543,] -0.0014745831675 0.0168475995 0 0 0.0092
## [544,] -0.0006361070839 0.0105063702 0 0 0.0048
## [545,] 0.0000408888582 0.0095435633 0 0 0.0028
## [546,] -0.0000696347745 0.0041271822 0 0 0.0024
## [547,] -0.0003016159757 0.0132625073 0 0 0.0016
## [548,] -0.0003787717722 0.0077347549 0 0 0.0036
## [549,] 0.0000452273365 0.0146965567 0 0 0.0028
## [550,] -0.0001839968120 0.0055955480 0 0 0.0016
## [551,] -0.0010246348262 0.0149371419 0 0 0.0072
## [552,] -0.0004855172743 0.0094275504 0 0 0.0040
## [553,] -0.0001992327056 0.0052306775 0 0 0.0016
## [554,] -0.0000076070734 0.0073707705 0 0 0.0028
## [555,] -0.0004891682491 0.0095059204 0 0 0.0040
## [556,] -0.0005629228757 0.0105098874 0 0 0.0040
## [557,] -0.0002284582434 0.0077787061 0 0 0.0028
## [558,] -0.0000735577569 0.0034262648 0 0 0.0020
## [559,] -0.0009263100172 0.0232772170 0 0 0.0064
## [560,] 0.0000536329211 0.0092001225 0 0 0.0024
## [561,] -0.0001151265463 0.0030646943 0 0 0.0024
## [562,] -0.0005018326014 0.0085583665 0 0 0.0052
## [563,] -0.0023649567739 0.0512298088 0 0 0.0084
## [564,] -0.0001080360399 0.0082114783 0 0 0.0028
## [565,] -0.0007649064669 0.0150676668 0 0 0.0044
## [566,] -0.0011768112331 0.0152790460 0 0 0.0072
## [567,] -0.0010541797771 0.0164917435 0 0 0.0060
## [568,] -0.0004216007664 0.0082206023 0 0 0.0036
## [569,] -0.0002533944481 0.0069875311 0 0 0.0020
## [570,] -0.0001039741458 0.0030096012 0 0 0.0012
## [571,] -0.0002156644572 0.0074072955 0 0 0.0032
## [572,] -0.0003036334218 0.0077212829 0 0 0.0024
## [573,] -0.0002931886891 0.0093605161 0 0 0.0040
## [574,] -0.0031158740919 0.0751803851 0 0 0.0048
## [575,] -0.0004469989932 0.0103006719 0 0 0.0036
## [576,] -0.0002178014571 0.0055046149 0 0 0.0032
## [577,] -0.0003440544531 0.0081789127 0 0 0.0024
## [578,] -0.0009992112983 0.0161819434 0 0 0.0056
## [579,] -0.0010931994983 0.0271275150 0 0 0.0040
## [580,] -0.0004587123969 0.0095044139 0 0 0.0028
## [581,] -0.0003643595273 0.0091229579 0 0 0.0048
## [582,] -0.0014422333098 0.0189312001 0 0 0.0080
## [583,] -0.0010645211071 0.0177910177 0 0 0.0060
## [584,] -0.0002038178753 0.0061789097 0 0 0.0032
## [585,] -0.0002587646463 0.0070692299 0 0 0.0020
## [586,] -0.0007416383438 0.0134253834 0 0 0.0052
## [587,] -0.0002006543757 0.0095076174 0 0 0.0028
## [588,] -0.0008205274530 0.0229587509 0 0 0.0028
## [589,] -0.0013501437960 0.0189963061 0 0 0.0068
## [590,] -0.0008507766213 0.0265859188 0 0 0.0048
## [591,] -0.0004224303208 0.0077514921 0 0 0.0032
## [592,] -0.0021636198059 0.0249288167 0 0 0.0108
## [593,] -0.0006398758089 0.0109735626 0 0 0.0056
## [594,] -0.0004923903916 0.0084685295 0 0 0.0052
## [595,] -0.0009679470447 0.0147737972 0 0 0.0060
## [596,] -0.0003581151466 0.0077023425 0 0 0.0028
## [597,] -0.0017422576399 0.0191686767 0 0 0.0096
## [598,] -0.0010295068175 0.0145774980 0 0 0.0060
## [599,] -0.0005020149141 0.0138303580 0 0 0.0044
## [600,] -0.0003396206775 0.0101866969 0 0 0.0048
## [601,] -0.0002507895013 0.0078282020 0 0 0.0016
## [602,] -0.0003107241164 0.0076757743 0 0 0.0024
## [603,] -0.0000825475120 0.0062226831 0 0 0.0020
## [604,] -0.0005915039721 0.0109059865 0 0 0.0056
## [605,] -0.0000394178038 0.0018708763 0 0 0.0008
## [606,] 0.0002231388720 0.0235072648 0 0 0.0040
## [607,] -0.0001105173651 0.0028232652 0 0 0.0016
## [608,] -0.0001188674484 0.0112376418 0 0 0.0032
## [609,] -0.0006410729345 0.0118538515 0 0 0.0048
## [610,] -0.0000885166074 0.0033872809 0 0 0.0012
## [611,] -0.0006583971611 0.0092315187 0 0 0.0060
## [612,] 0.0000331535942 0.0121198416 0 0 0.0052
## [613,] -0.0003519017677 0.0072902719 0 0 0.0040
## [614,] -0.0005442708400 0.0085045082 0 0 0.0056
## [615,] -0.0001106324928 0.0061216149 0 0 0.0024
## [616,] -0.0003883569372 0.0082142719 0 0 0.0028
## [617,] -0.0006500122915 0.0114465379 0 0 0.0052
## [618,] -0.0001901338324 0.0105966084 0 0 0.0028
## [619,] -0.0004942803241 0.0076728560 0 0 0.0052
## [620,] -0.0001394975764 0.0034979612 0 0 0.0024
## [621,] -0.0002521222940 0.0060943986 0 0 0.0020
## [622,] -0.0007444891697 0.0109571650 0 0 0.0068
## [623,] -0.0002939651587 0.0067035078 0 0 0.0032
## [624,] -0.0007639580848 0.0123059969 0 0 0.0044
## [625,] -0.0004354051236 0.0080887887 0 0 0.0036
## [626,] -0.0001260526871 0.0043520064 0 0 0.0024
## [627,] 0.0000609914917 0.0075923944 0 0 0.0028
## [628,] -0.0012146952887 0.0421256866 0 0 0.0052
## [629,] -0.0003725524441 0.0080505744 0 0 0.0024
## [630,] -0.0003125111588 0.0094986005 0 0 0.0028
## [631,] 0.0000434165783 0.0158067105 0 0 0.0040
## [632,] -0.0011591276776 0.0184460863 0 0 0.0064
## [633,] -0.0003854290197 0.0093107626 0 0 0.0020
## [634,] 0.0003953653056 0.0196281399 0 0 0.0032
## [635,] -0.0005230982705 0.0102037166 0 0 0.0036
## [636,] -0.0016773911299 0.0294515758 0 0 0.0064
## [637,] -0.0004453215712 0.0086741367 0 0 0.0036
## [638,] -0.0005505931425 0.0133351286 0 0 0.0040
## [639,] -0.0003407168032 0.0070169489 0 0 0.0028
## [640,] -0.0005981997772 0.0151084631 0 0 0.0056
## [641,] -0.0004197869045 0.0120446606 0 0 0.0052
## [642,] -0.0003799972881 0.0082375485 0 0 0.0028
## [643,] -0.0000126328579 0.0050522904 0 0 0.0016
## [644,] -0.0011468566084 0.0204591688 0 0 0.0052
## [645,] -0.0005271498782 0.0091592952 0 0 0.0048
## [646,] -0.0004117705586 0.0079575066 0 0 0.0044
## [647,] -0.0002610676687 0.0063330922 0 0 0.0020
## [648,] -0.0014111516336 0.0255021580 0 0 0.0068
## [649,] -0.0005795696980 0.0107535884 0 0 0.0044
## [650,] -0.0002398621582 0.0072036865 0 0 0.0032
## [651,] -0.0016046515382 0.0258154401 0 0 0.0064
## [652,] -0.0003915183411 0.0079059105 0 0 0.0032
## [653,] -0.0001383473850 0.0041730428 0 0 0.0020
## [654,] -0.0003198334585 0.0108386682 0 0 0.0016
## [655,] -0.0004277522796 0.0090951512 0 0 0.0024
## [656,] -0.0003295075370 0.0071500134 0 0 0.0032
## [657,] -0.0000513906770 0.0053324354 0 0 0.0020
## [658,] -0.0006255631058 0.0146364003 0 0 0.0032
## [659,] -0.0000201493719 0.0077072032 0 0 0.0028
## [660,] -0.0003317521673 0.0113406510 0 0 0.0044
## [661,] 0.0009074410949 0.0255243125 0 0 0.0024
## [662,] -0.0002441865886 0.0063093893 0 0 0.0024
## [663,] -0.0006085573943 0.0143737093 0 0 0.0032
## [664,] -0.0001149194613 0.0041075850 0 0 0.0008
## [665,] -0.0003166161328 0.0071923476 0 0 0.0032
## [666,] -0.0001151702110 0.0058683007 0 0 0.0020
## [667,] -0.0005233636379 0.0142265983 0 0 0.0048
## [668,] -0.0000053129604 0.0092791531 0 0 0.0012
## [669,] -0.0003175909956 0.0079801621 0 0 0.0028
## [670,] -0.0002703436664 0.0085590960 0 0 0.0028
## [671,] -0.0007669881213 0.0116915599 0 0 0.0048
## [672,] -0.0003299400590 0.0071931455 0 0 0.0028
## [673,] -0.0002612451666 0.0060137098 0 0 0.0032
## [674,] -0.0001487571942 0.0037781861 0 0 0.0028
## [675,] -0.0003580591523 0.0083387441 0 0 0.0020
## [676,] -0.0001124565844 0.0043949104 0 0 0.0016
## [677,] -0.0000621308371 0.0031065419 0 0 0.0004
## [678,] -0.0013609235045 0.0214463204 0 0 0.0076
## [679,] -0.0008382995363 0.0125213808 0 0 0.0060
## [680,] -0.0000948155485 0.0028019125 0 0 0.0012
## [681,] -0.0000042265281 0.0051297811 0 0 0.0016
## [682,] -0.0001661721218 0.0042626567 0 0 0.0024
## [683,] -0.0004955277275 0.0091639281 0 0 0.0040
## [684,] -0.0000330971490 0.0091535987 0 0 0.0032
## [685,] -0.0000896187516 0.0046881411 0 0 0.0020
## [686,] -0.0000794975622 0.0161472298 0 0 0.0056
## [687,] -0.0006988737262 0.0147401937 0 0 0.0040
## [688,] 0.0000547268869 0.0043881547 0 0 0.0008
## [689,] -0.0001032502986 0.0040989244 0 0 0.0020
## [690,] -0.0003928980018 0.0101337719 0 0 0.0048
## [691,] -0.0000219341499 0.0017044708 0 0 0.0012
## [692,] -0.0005522101773 0.0095731837 0 0 0.0040
## [693,] -0.0005484332866 0.0133251940 0 0 0.0020
## [694,] -0.0005262667964 0.0115930918 0 0 0.0040
## [695,] 0.0000511064789 0.0060496822 0 0 0.0020
## [696,] -0.0004944387057 0.0101525579 0 0 0.0052
## [697,] -0.0003288029889 0.0088661110 0 0 0.0020
## [698,] -0.0002866064954 0.0105307421 0 0 0.0044
## [699,] -0.0003150744605 0.0069054940 0 0 0.0024
## [700,] -0.0015159811379 0.0194263139 0 0 0.0072
## [701,] -0.0001650360290 0.0046250335 0 0 0.0024
## [702,] -0.0010092205386 0.0140863096 0 0 0.0068
## [703,] -0.0012741231127 0.0167388736 0 0 0.0088
## [704,] -0.0002235016145 0.0073659573 0 0 0.0036
## [705,] -0.0004012466029 0.0070121647 0 0 0.0040
## [706,] -0.0006560036347 0.0114761105 0 0 0.0040
## [707,] -0.0004752664648 0.0114021131 0 0 0.0032
## [708,] -0.0004858543557 0.0127275184 0 0 0.0036
## [709,] -0.0001912200685 0.0064462841 0 0 0.0016
## [710,] -0.0009151765626 0.0174158354 0 0 0.0044
## [711,] -0.0002099192193 0.0061727400 0 0 0.0024
## [712,] -0.0003286975460 0.0152042880 0 0 0.0048
## [713,] -0.0000827674534 0.0097490744 0 0 0.0028
## [714,] -0.0003832078142 0.0098801916 0 0 0.0028
## [715,] 0.0002594942768 0.0083304586 0 0 0.0036
## [716,] -0.0002441485711 0.0064377165 0 0 0.0016
## [717,] -0.0011989836688 0.0168790651 0 0 0.0076
## [718,] 0.0011718260235 0.0238856085 0 0 0.0048
## [719,] -0.0003962820550 0.0080611067 0 0 0.0064
## [720,] -0.0000207088391 0.0105012564 0 0 0.0032
## [721,] -0.0003510195043 0.0060685485 0 0 0.0040
## [722,] -0.0001702141274 0.0089938319 0 0 0.0028
## [723,] -0.0010036300584 0.0181058012 0 0 0.0056
## [724,] -0.0000693031440 0.0054339245 0 0 0.0016
## [725,] -0.0015081004305 0.0547225093 0 0 0.0036
## [726,] -0.0002438961823 0.0068370402 0 0 0.0020
## [727,] -0.0002647618966 0.0066395605 0 0 0.0028
## [728,] -0.0004948329627 0.0084727922 0 0 0.0044
## [729,] -0.0002756928968 0.0076930771 0 0 0.0020
## [730,] -0.0006504164058 0.0097073559 0 0 0.0064
priors.npb <- priors.npb.24
#' Exposures
colnames(X.scaled)
## [1] "mean_pm" "mean_o3" "mean_temp"
## [4] "pct_tree_cover" "pct_impervious" "mean_aadt_intensity"
## [7] "dist_m_tri" "dist_m_npl" "dist_m_waste_site"
## [10] "dist_m_major_emit" "dist_m_cafo" "dist_m_mine_well"
## [13] "cvd_rate_adj" "res_rate_adj" "violent_crime_rate"
## [16] "property_crime_rate" "pct_less_hs" "pct_unemp"
## [19] "pct_limited_eng" "pct_hh_pov" "pct_poc"
#' Covariates
colnames(W.scaled2)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "days_to_peapod"
# fit.npb2 <- npb(niter = 5000, nburn = 2500, X = X.scaled, Y = Y, W = W.scaled2,
# scaleY = TRUE,
# priors = priors.npb, interact = TRUE, XWinteract = TRUE)
# save(fit.npb2, file = here::here("Results", "NPB_Adiposity_v4.2.rdata"))
load(here::here("Results", "NPB_Adiposity_v4.2.rdata"))
npb.sum2 <- summary(fit.npb2)
rownames(npb.sum2$main.effects) <- colnames(X.scaled)
npb.sum2$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## mean_pm -0.010554538 0.05903028 -0.16333074 0.11178851 0.3220
## mean_o3 -0.023530384 0.08156296 -0.24121121 0.08924658 0.3632
## mean_temp -0.013282602 0.07266379 -0.19533371 0.11526919 0.3196
## pct_tree_cover -0.004871890 0.05652762 -0.14829777 0.11364760 0.2848
## pct_impervious -0.010040735 0.05058221 -0.15414596 0.08569021 0.2868
## mean_aadt_intensity 0.011691398 0.06471925 -0.07754752 0.21236435 0.2804
## dist_m_tri -0.010135761 0.05873838 -0.17254024 0.10916930 0.3212
## dist_m_npl -0.001117706 0.05693107 -0.12758056 0.13773078 0.2952
## dist_m_waste_site 0.027903454 0.09636118 -0.07349430 0.33890726 0.3280
## dist_m_major_emit 0.008850338 0.06691049 -0.08981583 0.19170876 0.2880
## dist_m_cafo -0.016016807 0.11912587 -0.23751183 0.13747493 0.3500
## dist_m_mine_well -0.030029747 0.07826655 -0.27154230 0.06711149 0.3772
## cvd_rate_adj -0.020366856 0.06758799 -0.22109638 0.08446738 0.3488
## res_rate_adj -0.024713719 0.06863747 -0.21481767 0.04805949 0.3456
## violent_crime_rate -0.011464748 0.05971514 -0.15773743 0.09280046 0.3152
## property_crime_rate -0.059763771 0.10534890 -0.34515935 0.03220730 0.4920
## pct_less_hs -0.014544239 0.06912506 -0.19692052 0.08763224 0.3228
## pct_unemp -0.034691504 0.09011085 -0.29959460 0.05359022 0.3744
## pct_limited_eng 0.004575868 0.06597523 -0.11695765 0.19130898 0.3060
## pct_hh_pov -0.021341634 0.06647317 -0.22039649 0.06215629 0.3280
## pct_poc -0.001717322 0.06092007 -0.12820623 0.14560599 0.2868
rownames(npb.sum2$covariates)[2:nrow(npb.sum2$covariates)] <- colnames(W.scaled2)
npb.sum2$covariates
## Posterior Mean SD 95% CI Lower 95% CI Upper
## <NA> 9.14615825 1.6222717 5.9693334748 12.2221925
## lat 0.09066092 2.3825149 -4.5881377072 4.7199367
## lon 0.19707139 1.1492926 -2.0274510183 2.4848101
## lat_lon_int 0.08417526 2.8616955 -5.5660571547 5.6527334
## latina_re -0.36683191 0.4084322 -1.1941814124 0.4386115
## black_re -0.18978606 0.4506326 -1.0816826234 0.6925398
## other_re -0.82737686 0.5844405 -1.9764948714 0.3145525
## ed_no_hs 1.24460473 0.6234286 -0.0009047448 2.5022924
## ed_hs 1.08985784 0.5790538 -0.0670480427 2.2397716
## ed_aa 0.88443121 0.5052571 -0.1257578035 1.8669674
## ed_4yr 0.14849104 0.4245698 -0.6969759225 1.0206463
## low_bmi -0.40573014 0.7750438 -1.9326553520 1.1050394
## ovwt_bmi 0.48531540 0.3390471 -0.1990245696 1.1432029
## obese_bmi 1.29559649 0.3882326 0.5437141309 2.0730288
## concep_spring 0.31051978 0.4183356 -0.5079955209 1.1423800
## concep_summer 0.03319268 0.4367950 -0.8364730737 0.8861254
## concep_fall -0.04850701 0.4281385 -0.8936753638 0.7938291
## concep_2010 0.28058244 1.6078708 -2.8074925265 3.3445299
## concep_2011 -0.21492527 1.5947758 -3.3203515954 2.8957529
## concep_2012 -0.47596540 1.6017599 -3.5803987918 2.7041033
## concep_2013 -0.20296484 1.6001568 -3.3185693835 2.8764681
## maternal_age 0.75035784 0.1900528 0.3712644762 1.1293495
## any_smoker -0.84903664 0.5252440 -1.8672677630 0.2063238
## smokeSH -0.09503957 0.3810473 -0.8437592149 0.6416853
## mean_cpss -0.02905138 0.1644967 -0.3661543020 0.2920969
## mean_epsd -0.20204128 0.1673659 -0.5289632788 0.1183508
## male -1.36493110 0.2731270 -1.9049216850 -0.8234426
## days_to_peapod 0.84123375 0.1413592 0.5596189977 1.1126430
Next, all of the interactions between exposures or between exposures and covariates
npb.sum2$interactions
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] 0.000200932651 0.016592127 0.000000000 0 0.0096
## [2,] -0.000417239433 0.005948661 0.000000000 0 0.0076
## [3,] -0.002209899186 0.015956065 0.000000000 0 0.0248
## [4,] -0.004951083674 0.027336154 -0.089701310 0 0.0444
## [5,] -0.000763524938 0.008360307 0.000000000 0 0.0108
## [6,] -0.001778670533 0.014551639 0.000000000 0 0.0212
## [7,] -0.001302053609 0.012922568 0.000000000 0 0.0164
## [8,] -0.007260017142 0.036857363 -0.129722911 0 0.0532
## [9,] -0.005250704449 0.029440034 -0.087866714 0 0.0440
## [10,] -0.002635455586 0.019157660 -0.014506969 0 0.0264
## [11,] -0.004121048497 0.026173905 -0.070553177 0 0.0340
## [12,] -0.002043120368 0.016024227 0.000000000 0 0.0220
## [13,] -0.000849944082 0.009626160 0.000000000 0 0.0120
## [14,] -0.001802414269 0.014841920 0.000000000 0 0.0188
## [15,] -0.000520578059 0.007810812 0.000000000 0 0.0080
## [16,] -0.002648159712 0.019660465 0.000000000 0 0.0256
## [17,] -0.004316207756 0.026610794 -0.077341251 0 0.0364
## [18,] -0.008170582676 0.041045525 -0.144403679 0 0.0516
## [19,] -0.001384151072 0.012105139 0.000000000 0 0.0184
## [20,] -0.002776660679 0.019802262 -0.028515003 0 0.0260
## [21,] -0.005074132751 0.027588401 -0.093780229 0 0.0424
## [22,] -0.000484188150 0.007058413 0.000000000 0 0.0108
## [23,] -0.000387098595 0.010163467 0.000000000 0 0.0092
## [24,] -0.000484178439 0.007223877 0.000000000 0 0.0076
## [25,] -0.003030865651 0.020027521 -0.048526743 0 0.0296
## [26,] -0.001995043812 0.014417745 0.000000000 0 0.0248
## [27,] -0.001604794675 0.013548171 0.000000000 0 0.0192
## [28,] -0.001301150667 0.012846616 0.000000000 0 0.0144
## [29,] -0.002196075350 0.015468308 0.000000000 0 0.0244
## [30,] -0.001461309522 0.012580696 0.000000000 0 0.0180
## [31,] -0.000611572332 0.008313341 0.000000000 0 0.0092
## [32,] 0.000001523759 0.012324325 0.000000000 0 0.0092
## [33,] -0.000487390734 0.007667958 0.000000000 0 0.0088
## [34,] -0.000453640058 0.006317269 0.000000000 0 0.0088
## [35,] -0.001987367980 0.016563851 0.000000000 0 0.0216
## [36,] -0.001282588899 0.012141274 0.000000000 0 0.0148
## [37,] -0.001297497317 0.010900081 0.000000000 0 0.0168
## [38,] -0.000739639279 0.009434261 0.000000000 0 0.0108
## [39,] -0.002216391312 0.015949275 0.000000000 0 0.0252
## [40,] -0.000644341414 0.007880546 0.000000000 0 0.0092
## [41,] -0.000982461625 0.010656603 0.000000000 0 0.0116
## [42,] -0.000262932977 0.007929560 0.000000000 0 0.0080
## [43,] -0.001518527938 0.013096100 0.000000000 0 0.0176
## [44,] -0.001189253372 0.010909099 0.000000000 0 0.0156
## [45,] -0.001047511447 0.011150225 0.000000000 0 0.0120
## [46,] -0.000667023072 0.008058427 0.000000000 0 0.0100
## [47,] -0.001602032899 0.013983775 0.000000000 0 0.0176
## [48,] -0.002925151585 0.021470198 -0.006347764 0 0.0252
## [49,] -0.000583043796 0.008358401 0.000000000 0 0.0084
## [50,] -0.000694242878 0.008539051 0.000000000 0 0.0116
## [51,] -0.001535991219 0.013439964 0.000000000 0 0.0172
## [52,] -0.000833975846 0.009839336 0.000000000 0 0.0096
## [53,] -0.002232797477 0.016544133 0.000000000 0 0.0244
## [54,] -0.001917236859 0.015637156 0.000000000 0 0.0196
## [55,] -0.002330737971 0.019893055 0.000000000 0 0.0204
## [56,] -0.000718320328 0.014512498 0.000000000 0 0.0152
## [57,] -0.003863482512 0.023512363 -0.065522951 0 0.0348
## [58,] -0.000747420271 0.012518655 0.000000000 0 0.0112
## [59,] -0.000681830335 0.009073508 0.000000000 0 0.0100
## [60,] -0.001172975312 0.011357493 0.000000000 0 0.0152
## [61,] -0.000841060518 0.010520042 0.000000000 0 0.0108
## [62,] -0.000704030622 0.008395191 0.000000000 0 0.0084
## [63,] 0.000009103939 0.011904153 0.000000000 0 0.0076
## [64,] -0.001574274468 0.013669059 0.000000000 0 0.0180
## [65,] -0.001777063245 0.015540210 0.000000000 0 0.0168
## [66,] -0.001580655814 0.015273202 0.000000000 0 0.0176
## [67,] -0.001591672233 0.014736178 0.000000000 0 0.0176
## [68,] -0.001275616081 0.012276326 0.000000000 0 0.0148
## [69,] -0.000520878478 0.007754518 0.000000000 0 0.0076
## [70,] -0.001847612893 0.015265109 0.000000000 0 0.0192
## [71,] -0.001491533142 0.012805930 0.000000000 0 0.0180
## [72,] -0.001822719578 0.015476221 0.000000000 0 0.0204
## [73,] -0.001120615665 0.010369454 0.000000000 0 0.0156
## [74,] -0.001809954791 0.014852134 0.000000000 0 0.0200
## [75,] -0.000375759398 0.007838150 0.000000000 0 0.0092
## [76,] -0.000181650233 0.004836506 0.000000000 0 0.0048
## [77,] -0.000403697672 0.006632782 0.000000000 0 0.0056
## [78,] -0.000397132724 0.009425533 0.000000000 0 0.0096
## [79,] -0.000406146618 0.006285601 0.000000000 0 0.0060
## [80,] -0.000902046582 0.009052346 0.000000000 0 0.0128
## [81,] -0.001210668294 0.011137687 0.000000000 0 0.0168
## [82,] -0.003272504072 0.023298412 -0.039568838 0 0.0292
## [83,] -0.003194449005 0.021115569 -0.054160585 0 0.0300
## [84,] -0.000294274286 0.006842663 0.000000000 0 0.0076
## [85,] -0.000772329485 0.008441025 0.000000000 0 0.0112
## [86,] -0.001101204318 0.011430180 0.000000000 0 0.0132
## [87,] -0.001715807584 0.014062521 0.000000000 0 0.0196
## [88,] -0.000944519215 0.011219465 0.000000000 0 0.0148
## [89,] -0.001043872963 0.009968551 0.000000000 0 0.0148
## [90,] -0.001878855952 0.015260122 0.000000000 0 0.0188
## [91,] -0.000323759345 0.004828726 0.000000000 0 0.0072
## [92,] -0.000970648886 0.010955258 0.000000000 0 0.0132
## [93,] -0.000200929659 0.006592702 0.000000000 0 0.0060
## [94,] -0.002234159135 0.017358536 0.000000000 0 0.0228
## [95,] -0.000758365137 0.009904605 0.000000000 0 0.0096
## [96,] -0.000899113358 0.008547880 0.000000000 0 0.0132
## [97,] -0.003994953533 0.025909188 -0.065471827 0 0.0328
## [98,] -0.002458537910 0.018045576 0.000000000 0 0.0244
## [99,] -0.001736991817 0.014625528 0.000000000 0 0.0184
## [100,] -0.000328860415 0.006692525 0.000000000 0 0.0064
## [101,] -0.002019264509 0.016008132 0.000000000 0 0.0212
## [102,] -0.002159849872 0.017026586 0.000000000 0 0.0220
## [103,] -0.001804695750 0.015777295 0.000000000 0 0.0184
## [104,] -0.001372174224 0.013892185 0.000000000 0 0.0148
## [105,] -0.002155020037 0.018405120 0.000000000 0 0.0212
## [106,] -0.001191383418 0.011465095 0.000000000 0 0.0160
## [107,] -0.000828898954 0.009714095 0.000000000 0 0.0112
## [108,] -0.001347424868 0.011890195 0.000000000 0 0.0156
## [109,] -0.000228423071 0.005004478 0.000000000 0 0.0040
## [110,] -0.001417319242 0.012562335 0.000000000 0 0.0156
## [111,] -0.000421397829 0.007990996 0.000000000 0 0.0072
## [112,] -0.000483864956 0.009487177 0.000000000 0 0.0100
## [113,] -0.002115593841 0.017030950 0.000000000 0 0.0236
## [114,] -0.001820041139 0.014184746 0.000000000 0 0.0212
## [115,] -0.000711138170 0.011906465 0.000000000 0 0.0108
## [116,] -0.000358599710 0.006695027 0.000000000 0 0.0068
## [117,] -0.000943636087 0.010428204 0.000000000 0 0.0116
## [118,] -0.000698842029 0.008034033 0.000000000 0 0.0104
## [119,] -0.000462806994 0.007364406 0.000000000 0 0.0072
## [120,] -0.000708549336 0.009156904 0.000000000 0 0.0076
## [121,] -0.001954649062 0.016266273 0.000000000 0 0.0192
## [122,] -0.000621179716 0.008813500 0.000000000 0 0.0076
## [123,] -0.001067083883 0.011192113 0.000000000 0 0.0120
## [124,] -0.000126982333 0.007093875 0.000000000 0 0.0072
## [125,] -0.000277164584 0.006409781 0.000000000 0 0.0072
## [126,] -0.000913424906 0.010290346 0.000000000 0 0.0128
## [127,] -0.000710908370 0.009157144 0.000000000 0 0.0096
## [128,] -0.001726410406 0.015422870 0.000000000 0 0.0172
## [129,] -0.000825410784 0.010356772 0.000000000 0 0.0096
## [130,] -0.001629034233 0.014492403 0.000000000 0 0.0176
## [131,] -0.000743206832 0.008801307 0.000000000 0 0.0116
## [132,] -0.000937848794 0.011601471 0.000000000 0 0.0112
## [133,] -0.001537769124 0.014450693 0.000000000 0 0.0176
## [134,] -0.000387571984 0.012952201 0.000000000 0 0.0108
## [135,] -0.001037415341 0.012573986 0.000000000 0 0.0136
## [136,] -0.001184645573 0.011047455 0.000000000 0 0.0152
## [137,] -0.002024575690 0.016231857 0.000000000 0 0.0212
## [138,] -0.001781075721 0.015027277 0.000000000 0 0.0188
## [139,] -0.001719756474 0.014754979 0.000000000 0 0.0180
## [140,] -0.002656576315 0.019072140 -0.029664423 0 0.0276
## [141,] -0.001075140087 0.010602449 0.000000000 0 0.0132
## [142,] -0.002002005562 0.016147122 0.000000000 0 0.0200
## [143,] -0.001207706803 0.011062856 0.000000000 0 0.0144
## [144,] -0.001748968936 0.013975950 0.000000000 0 0.0188
## [145,] -0.000167162235 0.007132984 0.000000000 0 0.0056
## [146,] -0.000653614772 0.011748253 0.000000000 0 0.0092
## [147,] -0.000520277861 0.009283671 0.000000000 0 0.0080
## [148,] -0.000867694145 0.009359295 0.000000000 0 0.0124
## [149,] -0.002015502124 0.015748391 0.000000000 0 0.0216
## [150,] -0.000311213297 0.004990427 0.000000000 0 0.0056
## [151,] -0.004183081407 0.026338211 -0.075141335 0 0.0384
## [152,] -0.003674073401 0.023428112 -0.063962073 0 0.0320
## [153,] -0.002551659728 0.018331102 0.000000000 0 0.0244
## [154,] -0.000820937412 0.008625549 0.000000000 0 0.0116
## [155,] -0.003316784165 0.022256688 -0.048656880 0 0.0296
## [156,] -0.002182029155 0.016176494 0.000000000 0 0.0236
## [157,] -0.000981946360 0.009704833 0.000000000 0 0.0128
## [158,] -0.001329466604 0.012557612 0.000000000 0 0.0148
## [159,] -0.000982496129 0.010112566 0.000000000 0 0.0108
## [160,] -0.001089522287 0.011416037 0.000000000 0 0.0124
## [161,] -0.000873085232 0.010011481 0.000000000 0 0.0124
## [162,] -0.000705175334 0.010377985 0.000000000 0 0.0112
## [163,] -0.001461234586 0.014427138 0.000000000 0 0.0176
## [164,] -0.001243811004 0.012112494 0.000000000 0 0.0144
## [165,] -0.001087713588 0.010553238 0.000000000 0 0.0140
## [166,] -0.000551196402 0.009914154 0.000000000 0 0.0104
## [167,] -0.000284049377 0.005968518 0.000000000 0 0.0052
## [168,] -0.000916676412 0.009698813 0.000000000 0 0.0124
## [169,] -0.000900981002 0.010414745 0.000000000 0 0.0104
## [170,] -0.000972380569 0.009957473 0.000000000 0 0.0120
## [171,] -0.000217632208 0.011410253 0.000000000 0 0.0060
## [172,] -0.000881683745 0.009468292 0.000000000 0 0.0108
## [173,] -0.000617161071 0.008858330 0.000000000 0 0.0084
## [174,] -0.000713888350 0.007762796 0.000000000 0 0.0124
## [175,] -0.006179059207 0.030433815 -0.112928162 0 0.0508
## [176,] -0.001309204245 0.012416815 0.000000000 0 0.0160
## [177,] -0.000750086640 0.010816268 0.000000000 0 0.0124
## [178,] -0.002044414758 0.015573866 0.000000000 0 0.0220
## [179,] -0.012171002542 0.056255529 -0.190281008 0 0.0652
## [180,] -0.001621892993 0.013629443 0.000000000 0 0.0196
## [181,] -0.002734978087 0.020820318 0.000000000 0 0.0252
## [182,] -0.002786627380 0.020693201 0.000000000 0 0.0248
## [183,] -0.000402296100 0.006153363 0.000000000 0 0.0056
## [184,] -0.000683428314 0.007913932 0.000000000 0 0.0100
## [185,] -0.001899366771 0.016712329 0.000000000 0 0.0188
## [186,] -0.002788741072 0.019878139 -0.024347564 0 0.0276
## [187,] -0.000908305186 0.009208490 0.000000000 0 0.0124
## [188,] -0.001213802050 0.011658764 0.000000000 0 0.0144
## [189,] -0.002527029710 0.019177870 0.000000000 0 0.0244
## [190,] -0.000018706644 0.000685062 0.000000000 0 0.0008
## [191,] -0.000385405291 0.005670880 0.000000000 0 0.0072
## [192,] -0.000220007827 0.003719605 0.000000000 0 0.0040
## [193,] -0.000272858575 0.004489052 0.000000000 0 0.0044
## [194,] 0.000013839093 0.002163730 0.000000000 0 0.0032
## [195,] -0.000350069288 0.008493509 0.000000000 0 0.0084
## [196,] -0.000447072471 0.008005554 0.000000000 0 0.0068
## [197,] -0.000895297096 0.010012999 0.000000000 0 0.0116
## [198,] -0.000320313517 0.014697541 0.000000000 0 0.0092
## [199,] -0.000280659097 0.006580318 0.000000000 0 0.0060
## [200,] -0.000618204527 0.008146822 0.000000000 0 0.0104
## [201,] -0.001925312829 0.014638563 0.000000000 0 0.0216
## [202,] -0.000549937080 0.006762561 0.000000000 0 0.0084
## [203,] -0.000755919320 0.009667065 0.000000000 0 0.0108
## [204,] -0.001252875161 0.012719645 0.000000000 0 0.0176
## [205,] -0.001962430981 0.014514785 0.000000000 0 0.0236
## [206,] -0.001359806594 0.012691772 0.000000000 0 0.0148
## [207,] -0.002529067452 0.019676510 0.000000000 0 0.0236
## [208,] -0.000716377021 0.008444234 0.000000000 0 0.0100
## [209,] -0.000624676620 0.007550074 0.000000000 0 0.0104
## [210,] -0.000705901863 0.007551269 0.000000000 0 0.0108
## [211,] -0.000508568273 0.008103911 0.000000000 0 0.0120
## [212,] -0.002103012013 0.015895106 0.000000000 0 0.0232
## [213,] -0.002942173018 0.021478623 -0.043619957 0 0.0304
## [214,] -0.001857419705 0.016410469 0.000000000 0 0.0172
## [215,] -0.002258545931 0.016592707 0.000000000 0 0.0256
## [216,] -0.002602993598 0.028179298 0.000000000 0 0.0192
## [217,] -0.000507291411 0.019480089 0.000000000 0 0.0132
## [218,] -0.002113496630 0.019343038 0.000000000 0 0.0176
## [219,] -0.003329689250 0.023204704 -0.047763767 0 0.0300
## [220,] -0.001035632673 0.014475393 0.000000000 0 0.0136
## [221,] -0.001929792447 0.018072637 0.000000000 0 0.0168
## [222,] -0.004546369409 0.029900579 -0.080661335 0 0.0336
## [223,] -0.001501891413 0.013732071 0.000000000 0 0.0152
## [224,] -0.000946408939 0.011625172 0.000000000 0 0.0132
## [225,] -0.002196271472 0.019839913 0.000000000 0 0.0200
## [226,] -0.003461630616 0.024245618 -0.045264763 0 0.0312
## [227,] -0.001683192703 0.017372853 0.000000000 0 0.0176
## [228,] -0.001539030657 0.014668432 0.000000000 0 0.0152
## [229,] -0.001606752920 0.014387561 0.000000000 0 0.0172
## [230,] -0.001740061351 0.014837874 0.000000000 0 0.0180
## [231,] -0.004663862425 0.026762494 -0.087009770 0 0.0388
## [232,] -0.001786843805 0.014255081 0.000000000 0 0.0204
## [233,] -0.000807690743 0.011550933 0.000000000 0 0.0096
## [234,] -0.000705959902 0.008636855 0.000000000 0 0.0100
## [235,] -0.000289229375 0.007724891 0.000000000 0 0.0076
## [236,] -0.001287312306 0.012250094 0.000000000 0 0.0160
## [237,] -0.001751767928 0.013575242 0.000000000 0 0.0212
## [238,] -0.000421593945 0.009110484 0.000000000 0 0.0100
## [239,] -0.004602665337 0.026609940 -0.078392707 0 0.0408
## [240,] -0.005958205345 0.032625690 -0.111322698 0 0.0440
## [241,] -0.001527475873 0.015954989 0.000000000 0 0.0144
## [242,] -0.001595005470 0.014041582 0.000000000 0 0.0172
## [243,] -0.001388162586 0.018142526 0.000000000 0 0.0172
## [244,] -0.001736999186 0.016573590 0.000000000 0 0.0176
## [245,] -0.001883531673 0.016810699 0.000000000 0 0.0232
## [246,] -0.003043889219 0.023154089 -0.008503630 0 0.0256
## [247,] -0.001292293073 0.015322364 0.000000000 0 0.0140
## [248,] -0.001842462750 0.016022724 0.000000000 0 0.0172
## [249,] -0.000528645885 0.013003300 0.000000000 0 0.0120
## [250,] -0.003961771808 0.032150602 -0.042387877 0 0.0280
## [251,] -0.008982202981 0.075778676 -0.088923047 0 0.0380
## [252,] -0.001743108642 0.015370176 0.000000000 0 0.0208
## [253,] -0.001371723167 0.012834508 0.000000000 0 0.0148
## [254,] -0.005313643840 0.054434858 -0.031770766 0 0.0276
## [255,] -0.001983665915 0.017907128 0.000000000 0 0.0208
## [256,] -0.001240765206 0.013388188 0.000000000 0 0.0160
## [257,] -0.001080481692 0.014322067 0.000000000 0 0.0168
## [258,] -0.000610220350 0.007879747 0.000000000 0 0.0104
## [259,] -0.002358018748 0.021086943 0.000000000 0 0.0188
## [260,] -0.004040785803 0.037888128 -0.024666455 0 0.0264
## [261,] -0.000377731396 0.008429854 0.000000000 0 0.0076
## [262,] -0.001285295116 0.011742380 0.000000000 0 0.0152
## [263,] -0.003157935893 0.026265562 0.000000000 0 0.0260
## [264,] -0.002515069352 0.017775228 0.000000000 0 0.0248
## [265,] -0.000455076231 0.006179497 0.000000000 0 0.0072
## [266,] -0.005588451459 0.031714112 -0.096165595 0 0.0408
## [267,] -0.004810597769 0.028647417 -0.090278494 0 0.0388
## [268,] -0.001409551749 0.013189737 0.000000000 0 0.0180
## [269,] -0.001362424974 0.018578734 0.000000000 0 0.0216
## [270,] -0.001935995546 0.017121688 0.000000000 0 0.0196
## [271,] -0.001472072153 0.020714889 0.000000000 0 0.0164
## [272,] -0.002995523005 0.021768859 -0.021095274 0 0.0264
## [273,] -0.002863103302 0.022345296 -0.006347764 0 0.0252
## [274,] -0.001172138601 0.011137216 0.000000000 0 0.0144
## [275,] -0.001862146020 0.018894578 0.000000000 0 0.0172
## [276,] -0.000541689736 0.010220443 0.000000000 0 0.0132
## [277,] -0.005977125134 0.043700397 -0.090003501 0 0.0392
## [278,] -0.009593671385 0.105466261 -0.072065256 0 0.0356
## [279,] -0.001839600848 0.015127303 0.000000000 0 0.0196
## [280,] -0.001489177051 0.015448905 0.000000000 0 0.0140
## [281,] -0.003004095498 0.022039847 -0.027236651 0 0.0284
## [282,] -0.001558000814 0.013397028 0.000000000 0 0.0200
## [283,] -0.001175671061 0.011970843 0.000000000 0 0.0140
## [284,] -0.001096764428 0.018247873 0.000000000 0 0.0152
## [285,] -0.000814265645 0.009246399 0.000000000 0 0.0108
## [286,] -0.001896766541 0.016909072 0.000000000 0 0.0180
## [287,] -0.003116593856 0.021009131 -0.051423676 0 0.0304
## [288,] -0.000748279666 0.010061054 0.000000000 0 0.0100
## [289,] -0.001036225333 0.010860211 0.000000000 0 0.0144
## [290,] -0.001935138586 0.016194354 0.000000000 0 0.0220
## [291,] -0.001830457860 0.015225543 0.000000000 0 0.0216
## [292,] -0.001494557707 0.012901037 0.000000000 0 0.0168
## [293,] -0.001082378080 0.010674799 0.000000000 0 0.0132
## [294,] -0.001199716715 0.011674993 0.000000000 0 0.0148
## [295,] -0.002009734212 0.017235822 0.000000000 0 0.0196
## [296,] -0.001085683857 0.017094241 0.000000000 0 0.0164
## [297,] -0.001789687300 0.015695813 0.000000000 0 0.0196
## [298,] -0.001978532284 0.017227585 0.000000000 0 0.0200
## [299,] -0.002126040262 0.018401175 0.000000000 0 0.0200
## [300,] -0.000984484942 0.012758970 0.000000000 0 0.0124
## [301,] -0.001865440868 0.014899905 0.000000000 0 0.0200
## [302,] -0.001860042970 0.018491230 0.000000000 0 0.0160
## [303,] -0.002139993934 0.016268888 0.000000000 0 0.0240
## [304,] -0.002008609425 0.015380976 0.000000000 0 0.0228
## [305,] -0.000908362711 0.010315962 0.000000000 0 0.0108
## [306,] -0.002376083009 0.018218020 0.000000000 0 0.0244
## [307,] -0.001227465486 0.012813150 0.000000000 0 0.0132
## [308,] -0.001365020997 0.014176959 0.000000000 0 0.0160
## [309,] -0.001395171691 0.015240654 0.000000000 0 0.0156
## [310,] -0.002701706454 0.021073718 0.000000000 0 0.0236
## [311,] -0.000663705395 0.008178744 0.000000000 0 0.0080
## [312,] -0.001551052433 0.012746226 0.000000000 0 0.0184
## [313,] -0.001434725206 0.013776326 0.000000000 0 0.0152
## [314,] -0.001408674224 0.014193461 0.000000000 0 0.0144
## [315,] -0.001619811106 0.014701926 0.000000000 0 0.0160
## [316,] -0.001416139114 0.012411547 0.000000000 0 0.0180
## [317,] -0.001014224495 0.012031676 0.000000000 0 0.0152
## [318,] -0.001644589404 0.013378469 0.000000000 0 0.0196
## [319,] -0.001418544507 0.012933412 0.000000000 0 0.0152
## [320,] -0.000908201968 0.008897872 0.000000000 0 0.0124
## [321,] -0.001108482513 0.010594918 0.000000000 0 0.0160
## [322,] -0.000686141893 0.015616408 0.000000000 0 0.0140
## [323,] -0.001516631495 0.014722330 0.000000000 0 0.0148
## [324,] -0.002488286866 0.021767903 0.000000000 0 0.0232
## [325,] -0.001382186312 0.014520913 0.000000000 0 0.0132
## [326,] -0.001933050073 0.019541284 0.000000000 0 0.0160
## [327,] -0.002018051375 0.017708794 0.000000000 0 0.0192
## [328,] -0.001092011521 0.016190750 0.000000000 0 0.0172
## [329,] -0.001774455658 0.017961751 0.000000000 0 0.0176
## [330,] -0.000627267632 0.011325502 0.000000000 0 0.0112
## [331,] -0.001198823113 0.012668863 0.000000000 0 0.0148
## [332,] -0.001681064604 0.015382230 0.000000000 0 0.0172
## [333,] -0.002290180880 0.018234302 0.000000000 0 0.0208
## [334,] -0.001252245045 0.012107970 0.000000000 0 0.0144
## [335,] -0.000713610392 0.016259788 0.000000000 0 0.0120
## [336,] -0.001107029703 0.016630124 0.000000000 0 0.0144
## [337,] -0.001861017261 0.015642107 0.000000000 0 0.0172
## [338,] -0.002676636681 0.019071945 0.000000000 0 0.0240
## [339,] -0.003099092438 0.021574604 -0.034727626 0 0.0288
## [340,] -0.002560409548 0.025156098 0.000000000 0 0.0228
## [341,] -0.002062709895 0.016737567 0.000000000 0 0.0204
## [342,] -0.003192416291 0.021735718 -0.053458965 0 0.0304
## [343,] -0.000674554829 0.007768183 0.000000000 0 0.0100
## [344,] -0.005119404727 0.035958173 -0.070105851 0 0.0368
## [345,] -0.001281122751 0.012769847 0.000000000 0 0.0152
## [346,] -0.002610218577 0.019529680 -0.008560454 0 0.0256
## [347,] -0.003491250316 0.022238910 -0.064236163 0 0.0336
## [348,] -0.001583334518 0.014567904 0.000000000 0 0.0180
## [349,] -0.000848428447 0.016360207 0.000000000 0 0.0132
## [350,] -0.002216033267 0.018858735 0.000000000 0 0.0212
## [351,] -0.001451108580 0.013848624 0.000000000 0 0.0188
## [352,] -0.001519539729 0.014274317 0.000000000 0 0.0152
## [353,] -0.002717503920 0.020062857 0.000000000 0 0.0248
## [354,] -0.001543341972 0.013329818 0.000000000 0 0.0180
## [355,] 0.000213015677 0.031096904 0.000000000 0 0.0112
## [356,] -0.001975611860 0.017257261 0.000000000 0 0.0192
## [357,] -0.000871058265 0.009201997 0.000000000 0 0.0132
## [358,] -0.001355722542 0.012903394 0.000000000 0 0.0160
## [359,] -0.000607004659 0.009115562 0.000000000 0 0.0120
## [360,] -0.001061891038 0.009781546 0.000000000 0 0.0144
## [361,] -0.002382233850 0.017038147 0.000000000 0 0.0256
## [362,] -0.001594204255 0.014468668 0.000000000 0 0.0176
## [363,] -0.000946869932 0.013402504 0.000000000 0 0.0136
## [364,] -0.000465878341 0.010162150 0.000000000 0 0.0096
## [365,] -0.001659127106 0.015909460 0.000000000 0 0.0172
## [366,] -0.001216996676 0.010730583 0.000000000 0 0.0164
## [367,] -0.002420434384 0.025630731 0.000000000 0 0.0180
## [368,] -0.002585955337 0.018477050 -0.023469931 0 0.0264
## [369,] -0.000902496449 0.010953496 0.000000000 0 0.0132
## [370,] -0.000783643292 0.009110700 0.000000000 0 0.0108
## [371,] -0.001844258551 0.017172358 0.000000000 0 0.0184
## [372,] -0.001056700574 0.010920305 0.000000000 0 0.0136
## [373,] -0.001673877999 0.014371410 0.000000000 0 0.0188
## [374,] -0.001188120816 0.011065709 0.000000000 0 0.0144
## [375,] -0.000768324020 0.010613475 0.000000000 0 0.0112
## [376,] -0.001535895833 0.013184471 0.000000000 0 0.0176
## [377,] -0.001167292842 0.012497580 0.000000000 0 0.0144
## [378,] -0.000658123458 0.029494765 0.000000000 0 0.0160
## [379,] -0.001043649583 0.011977600 0.000000000 0 0.0152
## [380,] -0.002213072216 0.018479498 0.000000000 0 0.0184
## [381,] -0.001660747915 0.015206092 0.000000000 0 0.0176
## [382,] -0.001096890828 0.011559386 0.000000000 0 0.0136
## [383,] -0.001752843896 0.015338673 0.000000000 0 0.0192
## [384,] -0.002067152510 0.017854198 0.000000000 0 0.0224
## [385,] -0.001784388927 0.014465640 0.000000000 0 0.0212
## [386,] -0.002343311779 0.021232394 0.000000000 0 0.0208
## [387,] -0.001424548489 0.015837773 0.000000000 0 0.0184
## [388,] -0.001112896593 0.011354081 0.000000000 0 0.0136
## [389,] -0.001596176287 0.016699706 0.000000000 0 0.0180
## [390,] -0.001504957230 0.014305534 0.000000000 0 0.0156
## [391,] -0.002019611422 0.017506518 0.000000000 0 0.0204
## [392,] -0.000836950293 0.011401426 0.000000000 0 0.0096
## [393,] -0.001268350457 0.011557917 0.000000000 0 0.0160
## [394,] -0.001662819242 0.014861886 0.000000000 0 0.0180
## [395,] -0.001567630822 0.014090504 0.000000000 0 0.0172
## [396,] -0.001690663435 0.014669358 0.000000000 0 0.0192
## [397,] -0.001010214158 0.010633696 0.000000000 0 0.0124
## [398,] -0.000842235434 0.009482582 0.000000000 0 0.0124
## [399,] -0.000885123387 0.010246714 0.000000000 0 0.0128
## [400,] -0.002190175459 0.015217433 0.000000000 0 0.0252
## [401,] -0.001893162827 0.014357881 0.000000000 0 0.0224
## [402,] -0.000540236841 0.011684281 0.000000000 0 0.0116
## [403,] -0.002753654266 0.021774305 -0.023607153 0 0.0264
## [404,] -0.000460813226 0.022546910 0.000000000 0 0.0104
## [405,] -0.001440955319 0.017586527 0.000000000 0 0.0176
## [406,] -0.001310526214 0.012725047 0.000000000 0 0.0160
## [407,] -0.001887728325 0.016896453 0.000000000 0 0.0184
## [408,] -0.001459165365 0.012679105 0.000000000 0 0.0164
## [409,] -0.001612179249 0.013707620 0.000000000 0 0.0164
## [410,] -0.003245044507 0.049412823 0.000000000 0 0.0204
## [411,] -0.000837901501 0.014060110 0.000000000 0 0.0148
## [412,] -0.002284671232 0.020596704 0.000000000 0 0.0184
## [413,] -0.001402276592 0.012559080 0.000000000 0 0.0164
## [414,] -0.001554558911 0.013899131 0.000000000 0 0.0196
## [415,] -0.001429066910 0.013955651 0.000000000 0 0.0148
## [416,] -0.001931432251 0.015954552 0.000000000 0 0.0200
## [417,] -0.001117649946 0.010539263 0.000000000 0 0.0140
## [418,] -0.002226184805 0.018088927 0.000000000 0 0.0216
## [419,] -0.000407032510 0.006989629 0.000000000 0 0.0064
## [420,] -0.001090387777 0.011462345 0.000000000 0 0.0136
## [421,] -0.001435070853 0.013808889 0.000000000 0 0.0156
## [422,] -0.001956016729 0.018315858 0.000000000 0 0.0184
## [423,] -0.000800115746 0.008666078 0.000000000 0 0.0108
## [424,] -0.001647896421 0.013761718 0.000000000 0 0.0192
## [425,] -0.000876576141 0.009068930 0.000000000 0 0.0116
## [426,] -0.001376321360 0.012599393 0.000000000 0 0.0176
## [427,] -0.008444296086 0.042606688 -0.126726903 0 0.0568
## [428,] -0.001918911816 0.016919349 0.000000000 0 0.0192
## [429,] -0.000154730370 0.007945233 0.000000000 0 0.0068
## [430,] -0.001534552259 0.013647197 0.000000000 0 0.0164
## [431,] -0.001437302078 0.012588391 0.000000000 0 0.0180
## [432,] -0.000567178617 0.021580919 0.000000000 0 0.0124
## [433,] -0.001332956828 0.012629080 0.000000000 0 0.0148
## [434,] -0.001593054567 0.013873196 0.000000000 0 0.0164
## [435,] -0.001045579904 0.010194639 0.000000000 0 0.0152
## [436,] -0.001186599652 0.011069914 0.000000000 0 0.0160
## [437,] -0.002090050922 0.016966870 0.000000000 0 0.0204
## [438,] -0.001251533861 0.013386735 0.000000000 0 0.0124
## [439,] -0.001756016953 0.015867579 0.000000000 0 0.0188
## [440,] -0.000216169114 0.024094423 0.000000000 0 0.0124
## [441,] -0.001329053624 0.012566764 0.000000000 0 0.0156
## [442,] -0.001202827555 0.013801395 0.000000000 0 0.0140
## [443,] -0.001403949388 0.014582134 0.000000000 0 0.0148
## [444,] -0.000709987427 0.012804438 0.000000000 0 0.0116
## [445,] -0.002261808570 0.018093809 0.000000000 0 0.0236
## [446,] -0.000212422695 0.022091112 0.000000000 0 0.0132
## [447,] -0.000748280105 0.008902237 0.000000000 0 0.0100
## [448,] -0.001224606064 0.013043342 0.000000000 0 0.0136
## [449,] -0.001522537350 0.013400958 0.000000000 0 0.0168
## [450,] -0.000331932937 0.006474230 0.000000000 0 0.0072
## [451,] -0.000684076822 0.010931862 0.000000000 0 0.0092
## [452,] -0.001139648211 0.011007912 0.000000000 0 0.0144
## [453,] -0.000971873390 0.010143247 0.000000000 0 0.0108
## [454,] -0.006761318136 0.033349741 -0.116885420 0 0.0528
## [455,] -0.004992414366 0.025915691 -0.097831262 0 0.0448
## [456,] -0.000535178452 0.011480750 0.000000000 0 0.0112
## [457,] -0.002292244292 0.017605935 0.000000000 0 0.0232
## [458,] -0.000708062611 0.007751826 0.000000000 0 0.0120
## [459,] -0.001742346736 0.015129649 0.000000000 0 0.0188
## [460,] -0.001735916629 0.014734763 0.000000000 0 0.0216
## [461,] -0.001448605949 0.013002296 0.000000000 0 0.0164
## [462,] -0.001401181736 0.014046846 0.000000000 0 0.0148
## [463,] -0.000731310621 0.010233693 0.000000000 0 0.0088
## [464,] -0.002027471520 0.017002738 0.000000000 0 0.0196
## [465,] -0.001084490761 0.011934266 0.000000000 0 0.0152
## [466,] -0.000743981991 0.010208731 0.000000000 0 0.0148
## [467,] -0.000986903391 0.011567494 0.000000000 0 0.0112
## [468,] -0.001957860813 0.017578189 0.000000000 0 0.0184
## [469,] -0.001258171646 0.011944700 0.000000000 0 0.0152
## [470,] -0.001242180941 0.014634941 0.000000000 0 0.0168
## [471,] -0.001534725722 0.014585589 0.000000000 0 0.0156
## [472,] -0.001522437304 0.014152183 0.000000000 0 0.0156
## [473,] -0.000799341956 0.010367321 0.000000000 0 0.0096
## [474,] -0.000664729458 0.008417515 0.000000000 0 0.0084
## [475,] -0.002012549074 0.016609704 0.000000000 0 0.0228
## [476,] -0.001473638368 0.018137130 0.000000000 0 0.0160
## [477,] -0.000569664106 0.007341963 0.000000000 0 0.0080
## [478,] -0.001131833952 0.010603781 0.000000000 0 0.0144
## [479,] -0.000985171261 0.011443256 0.000000000 0 0.0132
## [480,] -0.001411989661 0.013216555 0.000000000 0 0.0152
## [481,] -0.000619109081 0.007736107 0.000000000 0 0.0088
## [482,] -0.000389648815 0.006984129 0.000000000 0 0.0080
## [483,] -0.002069068883 0.015296137 0.000000000 0 0.0240
## [484,] -0.001293727699 0.014309402 0.000000000 0 0.0136
## [485,] -0.001490611556 0.013789520 0.000000000 0 0.0192
## [486,] -0.001869451201 0.017098833 0.000000000 0 0.0188
## [487,] -0.000686017831 0.008417035 0.000000000 0 0.0096
## [488,] -0.002989004580 0.021975896 -0.018480126 0 0.0264
## [489,] -0.001903384189 0.016113394 0.000000000 0 0.0184
## [490,] -0.001494552697 0.013390204 0.000000000 0 0.0172
## [491,] -0.002811430867 0.054575241 0.000000000 0 0.0200
## [492,] -0.000837534757 0.010644032 0.000000000 0 0.0108
## [493,] -0.002698271174 0.021149516 0.000000000 0 0.0224
## [494,] -0.001574290711 0.014344127 0.000000000 0 0.0164
## [495,] -0.002626490929 0.021678107 0.000000000 0 0.0264
## [496,] -0.001613049280 0.015770980 0.000000000 0 0.0164
## [497,] -0.001312509067 0.016360387 0.000000000 0 0.0144
## [498,] -0.001008772223 0.011978407 0.000000000 0 0.0132
## [499,] -0.002758013749 0.020647078 0.000000000 0 0.0244
## [500,] -0.001946092019 0.016884405 0.000000000 0 0.0196
## [501,] -0.001082041864 0.012339148 0.000000000 0 0.0168
## [502,] -0.001338949792 0.016340719 0.000000000 0 0.0124
## [503,] -0.001745684833 0.016382682 0.000000000 0 0.0172
## [504,] -0.001855682110 0.015637142 0.000000000 0 0.0192
## [505,] -0.001241121594 0.010833824 0.000000000 0 0.0176
## [506,] -0.002278512742 0.019392070 0.000000000 0 0.0200
## [507,] -0.001334340044 0.011943373 0.000000000 0 0.0160
## [508,] -0.000722067388 0.007803722 0.000000000 0 0.0096
## [509,] -0.000822312214 0.008938734 0.000000000 0 0.0112
## [510,] -0.001389120240 0.012205135 0.000000000 0 0.0172
## [511,] -0.001501698002 0.014272630 0.000000000 0 0.0156
## [512,] -0.001895005005 0.017184013 0.000000000 0 0.0188
## [513,] -0.001257720903 0.012915276 0.000000000 0 0.0128
## [514,] -0.001587812705 0.017893662 0.000000000 0 0.0160
## [515,] -0.003057818196 0.027067668 0.000000000 0 0.0236
## [516,] -0.001567228954 0.014559676 0.000000000 0 0.0188
## [517,] -0.002345298499 0.018197826 0.000000000 0 0.0240
## [518,] -0.002814163349 0.026449834 0.000000000 0 0.0240
## [519,] -0.002672529380 0.020539053 0.000000000 0 0.0248
## [520,] -0.002615527727 0.020423574 0.000000000 0 0.0248
## [521,] -0.001752249753 0.014761441 0.000000000 0 0.0208
## [522,] -0.003674285362 0.024906688 -0.050250642 0 0.0296
## [523,] -0.001264554638 0.011428430 0.000000000 0 0.0156
## [524,] -0.001264292767 0.012549911 0.000000000 0 0.0140
## [525,] -0.000813382329 0.009969337 0.000000000 0 0.0104
## [526,] -0.002785734847 0.020307474 -0.002599411 0 0.0252
## [527,] -0.002686496132 0.020716354 0.000000000 0 0.0244
## [528,] -0.001250989755 0.011925941 0.000000000 0 0.0144
## [529,] -0.001735347272 0.013994224 0.000000000 0 0.0216
## [530,] -0.001305018781 0.012399472 0.000000000 0 0.0148
## [531,] -0.002562949006 0.017438941 -0.036158461 0 0.0260
## [532,] -0.001139427132 0.010658459 0.000000000 0 0.0156
## [533,] -0.001783850997 0.014832096 0.000000000 0 0.0188
## [534,] -0.000887573474 0.010075185 0.000000000 0 0.0096
## [535,] -0.002186218494 0.017912574 0.000000000 0 0.0220
## [536,] -0.002324020276 0.017391592 0.000000000 0 0.0240
## [537,] -0.001150626621 0.011033842 0.000000000 0 0.0152
## [538,] -0.002171716897 0.018254673 0.000000000 0 0.0212
## [539,] -0.001249123143 0.010781458 0.000000000 0 0.0172
## [540,] -0.005190782950 0.061866755 -0.020164209 0 0.0264
## [541,] -0.002551167883 0.019108955 0.000000000 0 0.0236
## [542,] -0.002125104959 0.018020334 0.000000000 0 0.0228
## [543,] -0.000526472763 0.023854664 0.000000000 0 0.0116
## [544,] -0.002101314891 0.017833731 0.000000000 0 0.0204
## [545,] -0.001638970247 0.014288610 0.000000000 0 0.0176
## [546,] -0.000716462900 0.012484373 0.000000000 0 0.0132
## [547,] -0.001896091126 0.015980261 0.000000000 0 0.0192
## [548,] -0.002667840964 0.019472661 -0.032550232 0 0.0260
## [549,] -0.001541653493 0.016207597 0.000000000 0 0.0160
## [550,] -0.002958122112 0.022871599 0.000000000 0 0.0244
## [551,] -0.003227441100 0.029306136 0.000000000 0 0.0260
## [552,] -0.001376208672 0.013155157 0.000000000 0 0.0164
## [553,] -0.001122303040 0.011520243 0.000000000 0 0.0156
## [554,] -0.002338947125 0.020317820 0.000000000 0 0.0204
## [555,] -0.000916417111 0.009253832 0.000000000 0 0.0120
## [556,] -0.001649497476 0.013950398 0.000000000 0 0.0188
## [557,] -0.002184607882 0.020578027 0.000000000 0 0.0188
## [558,] -0.001050838638 0.010101100 0.000000000 0 0.0156
## [559,] -0.000966218150 0.009516971 0.000000000 0 0.0132
## [560,] -0.002316936923 0.019682974 0.000000000 0 0.0220
## [561,] -0.005235762913 0.030202041 -0.091184731 0 0.0396
## [562,] -0.001416528421 0.014283032 0.000000000 0 0.0164
## [563,] -0.001751702900 0.014938068 0.000000000 0 0.0180
## [564,] -0.001198003044 0.011660742 0.000000000 0 0.0140
## [565,] -0.002041460858 0.017806718 0.000000000 0 0.0220
## [566,] -0.001177447701 0.012133756 0.000000000 0 0.0152
## [567,] -0.003314356525 0.025129734 -0.040764258 0 0.0304
## [568,] -0.001444925036 0.017128200 0.000000000 0 0.0188
## [569,] -0.002455775675 0.021387634 0.000000000 0 0.0216
## [570,] -0.000966784597 0.010412129 0.000000000 0 0.0124
## [571,] -0.003769989738 0.027156829 -0.060921923 0 0.0300
## [572,] -0.001839536795 0.016278458 0.000000000 0 0.0188
## [573,] 0.000444112223 0.032283430 0.000000000 0 0.0136
## [574,] -0.002401838453 0.020824198 0.000000000 0 0.0212
## [575,] -0.001465703715 0.016136065 0.000000000 0 0.0160
## [576,] -0.001973736281 0.017258374 0.000000000 0 0.0204
## [577,] -0.002057832715 0.017090148 0.000000000 0 0.0220
## [578,] -0.002389904038 0.018422913 0.000000000 0 0.0244
## [579,] -0.001119372887 0.016613708 0.000000000 0 0.0164
## [580,] -0.000951351369 0.009860883 0.000000000 0 0.0140
## [581,] -0.001927585097 0.016484767 0.000000000 0 0.0196
## [582,] -0.001775039893 0.014676654 0.000000000 0 0.0200
## [583,] -0.002076654182 0.021119261 0.000000000 0 0.0200
## [584,] -0.002696130004 0.020772798 0.000000000 0 0.0244
## [585,] -0.001398262790 0.012570546 0.000000000 0 0.0188
## [586,] -0.001504907332 0.012470829 0.000000000 0 0.0188
## [587,] -0.002742334069 0.018813145 -0.026345090 0 0.0268
## [588,] -0.008240741993 0.042731733 -0.129691104 0 0.0560
## [589,] -0.001481605551 0.013840233 0.000000000 0 0.0164
## [590,] -0.006887188526 0.034986811 -0.116682272 0 0.0524
## [591,] -0.003228461196 0.022623789 -0.043102672 0 0.0280
## [592,] -0.000813168627 0.018840316 0.000000000 0 0.0168
## [593,] -0.001500321149 0.013411822 0.000000000 0 0.0164
## [594,] -0.002492603225 0.019581436 0.000000000 0 0.0252
## [595,] -0.002339248372 0.019951885 0.000000000 0 0.0216
## [596,] -0.000773114020 0.015568038 0.000000000 0 0.0144
## [597,] -0.001999033556 0.014961424 0.000000000 0 0.0228
## [598,] -0.004228626004 0.027379888 -0.067155155 0 0.0324
## [599,] -0.004916189886 0.096662317 0.000000000 0 0.0208
## [600,] -0.001500362383 0.013172693 0.000000000 0 0.0164
## [601,] -0.000748977814 0.010631270 0.000000000 0 0.0092
## [602,] -0.003311715191 0.025459296 0.000000000 0 0.0244
## [603,] -0.002983926694 0.020843014 -0.022807969 0 0.0272
## [604,] -0.001579496078 0.014412901 0.000000000 0 0.0176
## [605,] -0.002114419324 0.020531449 0.000000000 0 0.0216
## [606,] -0.003448575615 0.024429173 -0.040001438 0 0.0276
## [607,] -0.001257645653 0.013866839 0.000000000 0 0.0124
## [608,] -0.002685681807 0.019309541 0.000000000 0 0.0252
## [609,] -0.001565934224 0.014673011 0.000000000 0 0.0192
## [610,] -0.002896710606 0.040356124 0.000000000 0 0.0208
## [611,] -0.001296867086 0.014640367 0.000000000 0 0.0168
## [612,] -0.003488353466 0.024240266 -0.048322034 0 0.0280
## [613,] -0.004843374877 0.028617392 -0.081716306 0 0.0376
## [614,] -0.002957842429 0.023930207 0.000000000 0 0.0260
## [615,] -0.003542640377 0.026825675 -0.044273178 0 0.0300
## [616,] -0.001897044428 0.016057653 0.000000000 0 0.0188
## [617,] -0.001188916818 0.010859165 0.000000000 0 0.0140
## [618,] -0.001403305591 0.012779202 0.000000000 0 0.0160
## [619,] -0.002296481977 0.017917157 0.000000000 0 0.0228
## [620,] -0.001576714076 0.013969660 0.000000000 0 0.0168
## [621,] -0.004294410803 0.107327609 0.000000000 0 0.0164
## [622,] -0.000136596945 0.044399976 0.000000000 0 0.0144
## [623,] -0.001458178066 0.016144716 0.000000000 0 0.0172
## [624,] -0.002038053842 0.019364801 0.000000000 0 0.0188
## [625,] -0.003361228384 0.022872376 -0.048156248 0 0.0300
## [626,] -0.002197378476 0.023930528 0.000000000 0 0.0208
## [627,] -0.001659493087 0.016568396 0.000000000 0 0.0172
## [628,] -0.000690943178 0.014303920 0.000000000 0 0.0120
## [629,] -0.004467168701 0.032360623 -0.070593225 0 0.0336
## [630,] -0.004817214717 0.040120921 -0.067987610 0 0.0344
## [631,] -0.000893424553 0.010885265 0.000000000 0 0.0120
## [632,] -0.002538284039 0.018803459 0.000000000 0 0.0248
## [633,] -0.003020022068 0.023579216 -0.008560454 0 0.0260
## [634,] -0.002400614335 0.019846108 0.000000000 0 0.0216
## [635,] -0.003779637966 0.024467038 -0.072673879 0 0.0324
## [636,] -0.005756886486 0.030835012 -0.104446525 0 0.0472
## [637,] -0.002915125081 0.026119737 0.000000000 0 0.0248
## [638,] -0.001928416790 0.018426686 0.000000000 0 0.0180
## [639,] -0.006102895490 0.037721808 -0.095946669 0 0.0404
## [640,] -0.002785471546 0.018506743 -0.042282730 0 0.0308
## [641,] -0.002775946460 0.020151373 -0.020246345 0 0.0264
## [642,] -0.003062313980 0.027539662 0.000000000 0 0.0204
## [643,] -0.000676561935 0.008686938 0.000000000 0 0.0104
## [644,] -0.006174001824 0.033317637 -0.110436386 0 0.0476
## [645,] -0.003934147392 0.025912881 -0.062478852 0 0.0332
## [646,] -0.000928576297 0.011697480 0.000000000 0 0.0104
## [647,] -0.001847919307 0.015422125 0.000000000 0 0.0192
## [648,] -0.001217025705 0.011482556 0.000000000 0 0.0144
## [649,] -0.002289811791 0.023520589 0.000000000 0 0.0196
## [650,] -0.001147313607 0.014916189 0.000000000 0 0.0136
## [651,] -0.001853837200 0.018351995 0.000000000 0 0.0176
## [652,] -0.001436948962 0.014197762 0.000000000 0 0.0152
## [653,] -0.001240785396 0.033129340 0.000000000 0 0.0168
## [654,] -0.001064867702 0.010285178 0.000000000 0 0.0148
## [655,] -0.001248524705 0.013050588 0.000000000 0 0.0136
## [656,] -0.003271887373 0.022977481 -0.049157460 0 0.0288
## [657,] -0.000894136950 0.009915520 0.000000000 0 0.0100
## [658,] -0.001841883108 0.015230362 0.000000000 0 0.0204
## [659,] -0.000712257368 0.013531871 0.000000000 0 0.0104
## [660,] -0.002114636421 0.018045112 0.000000000 0 0.0204
## [661,] -0.001378434278 0.012222340 0.000000000 0 0.0164
## [662,] -0.001437001785 0.014810525 0.000000000 0 0.0148
## [663,] -0.001061959364 0.011190245 0.000000000 0 0.0128
## [664,] -0.002966749305 0.024962998 0.000000000 0 0.0248
## [665,] -0.001839635087 0.015337371 0.000000000 0 0.0188
## [666,] -0.001259841196 0.011359171 0.000000000 0 0.0160
## [667,] -0.001449509943 0.012954402 0.000000000 0 0.0164
## [668,] -0.003511605565 0.026140410 -0.056732529 0 0.0304
## [669,] -0.002855862793 0.019982705 -0.035420297 0 0.0284
## [670,] -0.001377391256 0.013012787 0.000000000 0 0.0172
## [671,] -0.003611686682 0.025340885 -0.049051406 0 0.0300
## [672,] -0.002559426761 0.021224625 0.000000000 0 0.0216
## [673,] -0.002224687207 0.022324240 0.000000000 0 0.0188
## [674,] -0.001119488630 0.010991796 0.000000000 0 0.0136
## [675,] -0.003326631113 0.028502315 0.000000000 0 0.0252
## [676,] -0.002132156509 0.018282459 0.000000000 0 0.0200
## [677,] -0.001645442602 0.016557288 0.000000000 0 0.0180
## [678,] -0.001080372012 0.010499248 0.000000000 0 0.0136
## [679,] -0.003597708808 0.028985658 -0.042305705 0 0.0292
## [680,] -0.002032728566 0.028201603 0.000000000 0 0.0192
## [681,] -0.000392666453 0.018843687 0.000000000 0 0.0132
## [682,] -0.001368380824 0.012670927 0.000000000 0 0.0160
## [683,] -0.004322609307 0.031045909 -0.058727811 0 0.0308
## [684,] -0.001455560731 0.016934423 0.000000000 0 0.0196
## [685,] -0.001864488359 0.014546199 0.000000000 0 0.0236
## [686,] -0.001442148771 0.013394054 0.000000000 0 0.0160
## [687,] -0.002854371311 0.021482624 0.000000000 0 0.0260
## [688,] -0.001105332820 0.012360506 0.000000000 0 0.0140
## [689,] -0.002022390724 0.015589621 0.000000000 0 0.0228
## [690,] -0.001454213628 0.013590255 0.000000000 0 0.0148
## [691,] -0.002254928857 0.017917670 0.000000000 0 0.0224
## [692,] -0.001515559586 0.014091267 0.000000000 0 0.0156
## [693,] -0.002246465475 0.018118800 0.000000000 0 0.0232
## [694,] -0.001398236050 0.012253929 0.000000000 0 0.0172
## [695,] -0.004666866470 0.030747639 -0.081352764 0 0.0368
## [696,] -0.003446185880 0.021683088 -0.061974032 0 0.0332
## [697,] -0.001458545489 0.013641927 0.000000000 0 0.0160
## [698,] -0.005237227210 0.032090797 -0.086269286 0 0.0396
## [699,] -0.002104766608 0.017923831 0.000000000 0 0.0220
## [700,] -0.000998748053 0.011398706 0.000000000 0 0.0132
## [701,] -0.001522911092 0.013551048 0.000000000 0 0.0168
## [702,] -0.002014298590 0.020625917 0.000000000 0 0.0188
## [703,] -0.001636439458 0.016182344 0.000000000 0 0.0152
## [704,] -0.001160966004 0.012690965 0.000000000 0 0.0168
## [705,] -0.001353426401 0.011993056 0.000000000 0 0.0168
## [706,] -0.000466348023 0.012439117 0.000000000 0 0.0120
## [707,] -0.002729307038 0.021734114 0.000000000 0 0.0236
## [708,] -0.000224573576 0.018631667 0.000000000 0 0.0112
## [709,] -0.000801772366 0.009593489 0.000000000 0 0.0100
## [710,] -0.002871321194 0.023180409 0.000000000 0 0.0240
## [711,] -0.001448587962 0.014671867 0.000000000 0 0.0132
## [712,] -0.001569633054 0.013788812 0.000000000 0 0.0152
## [713,] -0.000084139628 0.022137636 0.000000000 0 0.0128
## [714,] -0.001791183042 0.016576771 0.000000000 0 0.0204
## [715,] -0.001166135272 0.011038585 0.000000000 0 0.0160
## [716,] -0.001654114954 0.014996733 0.000000000 0 0.0172
## [717,] -0.001051500765 0.010519977 0.000000000 0 0.0132
## [718,] -0.002515160161 0.020677659 0.000000000 0 0.0252
## [719,] -0.001205537302 0.010796101 0.000000000 0 0.0152
## [720,] -0.001491676756 0.013510236 0.000000000 0 0.0184
## [721,] -0.001070300825 0.010869983 0.000000000 0 0.0136
## [722,] -0.001539930563 0.014438024 0.000000000 0 0.0180
## [723,] -0.001196460676 0.011795563 0.000000000 0 0.0136
## [724,] -0.001515873535 0.014014958 0.000000000 0 0.0152
## [725,] -0.003399083012 0.021568979 -0.047850389 0 0.0340
## [726,] -0.002755370323 0.022618981 0.000000000 0 0.0220
## [727,] -0.000860488517 0.010017921 0.000000000 0 0.0132
## [728,] -0.001107961287 0.013603288 0.000000000 0 0.0120
## [729,] -0.001806163001 0.016093696 0.000000000 0 0.0192
## [730,] -0.002135021788 0.016506656 0.000000000 0 0.0232
## [731,] -0.001074515462 0.011116523 0.000000000 0 0.0140
## [732,] -0.002191157050 0.019301357 0.000000000 0 0.0240
## [733,] -0.001863221347 0.015537532 0.000000000 0 0.0236
## [734,] -0.002445686880 0.018903981 0.000000000 0 0.0232
## [735,] -0.001009014042 0.010466014 0.000000000 0 0.0128
## [736,] -0.000898468320 0.010808528 0.000000000 0 0.0112
## [737,] -0.002286490026 0.017423190 0.000000000 0 0.0240
## [738,] -0.001208216462 0.013319360 0.000000000 0 0.0148
## [739,] -0.003900564801 0.030180685 -0.050958622 0 0.0292
## [740,] -0.002758464403 0.021433569 -0.021833707 0 0.0280
## [741,] -0.001867016433 0.015846165 0.000000000 0 0.0184
## [742,] -0.001134296535 0.013696975 0.000000000 0 0.0136
## [743,] -0.002154757650 0.019035408 0.000000000 0 0.0200
## [744,] -0.001229940992 0.013022243 0.000000000 0 0.0140
## [745,] -0.002315205442 0.020512701 0.000000000 0 0.0228
## [746,] -0.002213009525 0.018385090 0.000000000 0 0.0204
## [747,] -0.003552733066 0.021878727 -0.065332991 0 0.0320
## [748,] -0.001854739383 0.013486054 0.000000000 0 0.0224
## [749,] -0.004158913248 0.028113151 -0.064572818 0 0.0328
## [750,] -0.004739238321 0.028300050 -0.081011856 0 0.0392
## [751,] -0.001215836299 0.011772638 0.000000000 0 0.0156
## [752,] -0.002867396635 0.019785976 -0.046990064 0 0.0284
## [753,] -0.002842023612 0.022158623 -0.031124386 0 0.0276
## [754,] -0.001032344628 0.010488587 0.000000000 0 0.0140
## [755,] -0.001431813039 0.014002182 0.000000000 0 0.0168
## [756,] -0.001743843020 0.016548575 0.000000000 0 0.0184
## [757,] -0.002559551559 0.018909407 0.000000000 0 0.0240
## [758,] -0.001464013802 0.015933172 0.000000000 0 0.0160
## [759,] -0.000941214676 0.010516382 0.000000000 0 0.0116
## [760,] -0.001265758585 0.012268412 0.000000000 0 0.0140
## [761,] -0.001784309742 0.017072805 0.000000000 0 0.0164
## [762,] -0.001075238481 0.013336445 0.000000000 0 0.0112
## [763,] -0.001514307986 0.013848726 0.000000000 0 0.0156
## [764,] -0.003556564322 0.024044291 -0.054830614 0 0.0304
## [765,] 0.000779691560 0.035446358 0.000000000 0 0.0080
## [766,] -0.002512467615 0.018231914 0.000000000 0 0.0252
## [767,] -0.000777365458 0.014229808 0.000000000 0 0.0152
## [768,] -0.001647301563 0.018719264 0.000000000 0 0.0172
## [769,] -0.001206339221 0.012861724 0.000000000 0 0.0144
## [770,] -0.003013006649 0.024662032 -0.019485114 0 0.0268
## [771,] -0.001100007972 0.010445468 0.000000000 0 0.0152
## [772,] -0.003251109148 0.030860728 0.000000000 0 0.0212
## [773,] -0.002004827286 0.017827829 0.000000000 0 0.0188
## [774,] -0.001152901258 0.010194215 0.000000000 0 0.0164
## [775,] -0.001231707633 0.013570668 0.000000000 0 0.0120
## [776,] -0.002572007939 0.020403281 0.000000000 0 0.0236
## [777,] -0.002776826858 0.019970924 -0.024102091 0 0.0280
Because race/ethnicity might be on the causal pathway (mediator), we want to see if anything shows up when we exclude those variables from the model
priors.npb <- priors.npb.24
#' Exposures
colnames(X.scaled)
## [1] "mean_pm" "mean_o3" "mean_temp"
## [4] "pct_tree_cover" "pct_impervious" "mean_aadt_intensity"
## [7] "dist_m_tri" "dist_m_npl" "dist_m_waste_site"
## [10] "dist_m_major_emit" "dist_m_cafo" "dist_m_mine_well"
## [13] "cvd_rate_adj" "res_rate_adj" "violent_crime_rate"
## [16] "property_crime_rate" "pct_less_hs" "pct_unemp"
## [19] "pct_limited_eng" "pct_hh_pov" "pct_poc"
#' Covariates
colnames(W.scaled2)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "days_to_peapod"
# fit.npb3 <- npb(niter = 5000, nburn = 2500, X = X.scaled[,-c(3)], Y = Y, W = W.scaled2[,-c(4:6)],
# scaleY = TRUE,
# priors = priors.npb, interact = TRUE, XWinteract = TRUE)
# save(fit.npb3, file = here::here("Results", "NPB_Adiposity_v4a.1.rdata"))
load(here::here("Results", "NPB_Adiposity_v4a.1.rdata"))
npb.sum3 <- summary(fit.npb3)
rownames(npb.sum3$main.effects) <- colnames(X.scaled[,-c(3)])
npb.sum3$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## mean_pm -0.012631762 0.05528734 -0.16865861 0.07729421 0.2676
## mean_o3 -0.034175779 0.08978837 -0.27926198 0.05982863 0.3592
## pct_tree_cover -0.008806492 0.05449876 -0.15798453 0.09438554 0.2580
## pct_impervious -0.015696129 0.05739704 -0.17754353 0.05755177 0.2716
## mean_aadt_intensity 0.011216799 0.06452326 -0.08090708 0.22588466 0.2424
## dist_m_tri -0.013271220 0.05910733 -0.16694697 0.09109124 0.2876
## dist_m_npl -0.004693099 0.05488418 -0.13719647 0.12539949 0.2536
## dist_m_waste_site 0.028018679 0.09889330 -0.07327447 0.36237371 0.2844
## dist_m_major_emit 0.001054655 0.05324843 -0.10776088 0.14801417 0.2316
## dist_m_cafo -0.019398321 0.10014041 -0.24332798 0.11522828 0.3160
## dist_m_mine_well -0.035643689 0.08414809 -0.25890102 0.04895471 0.3656
## cvd_rate_adj -0.028467006 0.07506970 -0.24624291 0.04341892 0.3352
## res_rate_adj -0.030021658 0.07570491 -0.26084700 0.04621521 0.3408
## violent_crime_rate -0.015966384 0.05377350 -0.16337898 0.05514798 0.2880
## property_crime_rate -0.070054166 0.11175110 -0.36720111 0.01610051 0.4932
## pct_less_hs -0.025306998 0.07520270 -0.24662765 0.05368069 0.3148
## pct_unemp -0.046480601 0.09710954 -0.34433680 0.02897601 0.3864
## pct_limited_eng 0.000138379 0.06537619 -0.12528219 0.16858018 0.2612
## pct_hh_pov -0.028241196 0.07842328 -0.25016808 0.04726586 0.3216
## pct_poc -0.005169879 0.06528859 -0.15475411 0.13224523 0.2604
npb.sum3$main.effects$exp <- rownames(npb.sum3$main.effects)
## Warning in npb.sum3$main.effects$exp <- rownames(npb.sum3$main.effects):
## Coercing LHS to a list
write_csv(as.data.frame(npb.sum3$main.effects), here::here("Results", "NPB_Main_Effects_Adiposity_v4a.csv"))
rownames(npb.sum3$covariates)[2:nrow(npb.sum3$covariates)] <- colnames(W.scaled2[,-c(4:6)])
npb.sum3$covariates
## Posterior Mean SD 95% CI Lower 95% CI Upper
## <NA> 9.06347607 1.6365662 5.9131410 12.1950607
## lat 0.02709920 2.4708420 -5.2283534 4.8588264
## lon 0.23942267 1.1953225 -2.0661707 2.7098027
## lat_lon_int 0.01187645 2.9696994 -6.2972810 5.6693785
## ed_no_hs 1.08497941 0.6215179 -0.1355676 2.3414260
## ed_hs 0.94680709 0.5493252 -0.1281063 2.0319590
## ed_aa 0.76528715 0.4809650 -0.1429599 1.7204224
## ed_4yr 0.13805175 0.4324668 -0.7377975 0.9875152
## low_bmi -0.41470616 0.7761377 -1.8871789 1.1169196
## ovwt_bmi 0.46253943 0.3330042 -0.1878114 1.1341149
## obese_bmi 1.26784825 0.3829622 0.4932205 2.0192973
## concep_spring 0.28842849 0.4112400 -0.5196661 1.1321624
## concep_summer 0.03089214 0.4194164 -0.8256790 0.8286082
## concep_fall -0.03792696 0.4098549 -0.8753558 0.7494811
## concep_2010 0.28927586 1.6273817 -2.8857421 3.4676361
## concep_2011 -0.22168871 1.6231419 -3.4258334 2.9270462
## concep_2012 -0.50847891 1.6191316 -3.6813370 2.6781784
## concep_2013 -0.23580940 1.6166652 -3.4053886 2.9896366
## maternal_age 0.78307744 0.1842911 0.4252200 1.1429602
## any_smoker -0.78832009 0.5298167 -1.8277442 0.2839424
## smokeSH -0.08141143 0.3814158 -0.8427309 0.6538570
## mean_cpss -0.04327545 0.1663669 -0.3757894 0.2780126
## mean_epsd -0.20689302 0.1689163 -0.5472272 0.1145785
## male -1.38009212 0.2688158 -1.9123140 -0.8586457
## days_to_peapod 0.83030817 0.1417007 0.5457507 1.1143487
npb.sum3$covariates$covar <- rownames(npb.sum3$covariates)
## Warning in npb.sum3$covariates$covar <- rownames(npb.sum3$covariates): Coercing
## LHS to a list
write_csv(as.data.frame(npb.sum3$covariates), here::here("Results", "NPB_Covariate_Effects_Adiposity_v4a.csv"))
Next, all of the interactions between exposures or between exposures and covariates
npb.sum3$interactions
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] 0.000007369012 0.007785004 0.00000000 0 0.0040
## [2,] -0.001087185637 0.011445499 0.00000000 0 0.0116
## [3,] -0.003859248800 0.026494688 -0.03914222 0 0.0296
## [4,] -0.000343655421 0.007567538 0.00000000 0 0.0044
## [5,] -0.000495833664 0.007665230 0.00000000 0 0.0076
## [6,] -0.000706795560 0.008687952 0.00000000 0 0.0088
## [7,] -0.004573708763 0.030147252 -0.06402255 0 0.0304
## [8,] -0.003235470019 0.026098313 0.00000000 0 0.0212
## [9,] -0.001554260470 0.014682955 0.00000000 0 0.0148
## [10,] -0.001707048981 0.014642520 0.00000000 0 0.0172
## [11,] -0.001082329141 0.011542653 0.00000000 0 0.0124
## [12,] -0.000568599567 0.009724079 0.00000000 0 0.0092
## [13,] -0.000509434550 0.007752006 0.00000000 0 0.0060
## [14,] -0.000551156430 0.007672694 0.00000000 0 0.0076
## [15,] -0.002354826900 0.020096119 0.00000000 0 0.0208
## [16,] -0.002183197736 0.020153000 0.00000000 0 0.0196
## [17,] -0.003906072546 0.027663953 -0.03639852 0 0.0272
## [18,] -0.000867730308 0.010553016 0.00000000 0 0.0112
## [19,] -0.001155643381 0.013407614 0.00000000 0 0.0120
## [20,] -0.000689731704 0.008837173 0.00000000 0 0.0096
## [21,] -0.000295983374 0.007129817 0.00000000 0 0.0080
## [22,] -0.000336119011 0.005270125 0.00000000 0 0.0048
## [23,] -0.002631918077 0.022244416 0.00000000 0 0.0192
## [24,] -0.000951145801 0.010181161 0.00000000 0 0.0116
## [25,] -0.001075157094 0.012498368 0.00000000 0 0.0120
## [26,] -0.001134240818 0.012176631 0.00000000 0 0.0136
## [27,] -0.001670493825 0.015491508 0.00000000 0 0.0156
## [28,] -0.001083073340 0.011687012 0.00000000 0 0.0144
## [29,] -0.000334112249 0.006128716 0.00000000 0 0.0052
## [30,] -0.000188054069 0.005409133 0.00000000 0 0.0052
## [31,] -0.000160919850 0.004541450 0.00000000 0 0.0060
## [32,] -0.000133410178 0.003048737 0.00000000 0 0.0036
## [33,] -0.001077500621 0.012335497 0.00000000 0 0.0108
## [34,] -0.001013471496 0.010965478 0.00000000 0 0.0108
## [35,] -0.001171112068 0.012906853 0.00000000 0 0.0104
## [36,] -0.000237453579 0.006027415 0.00000000 0 0.0076
## [37,] -0.001642430405 0.016883565 0.00000000 0 0.0164
## [38,] -0.000301997014 0.006520882 0.00000000 0 0.0076
## [39,] -0.000419401469 0.008622383 0.00000000 0 0.0064
## [40,] -0.000643937226 0.007912578 0.00000000 0 0.0112
## [41,] -0.000616892821 0.007391041 0.00000000 0 0.0088
## [42,] -0.000466932176 0.007768467 0.00000000 0 0.0076
## [43,] 0.000058730857 0.010033782 0.00000000 0 0.0068
## [44,] -0.000673744652 0.008169369 0.00000000 0 0.0096
## [45,] -0.000519171424 0.008328063 0.00000000 0 0.0080
## [46,] -0.000570042776 0.008465747 0.00000000 0 0.0072
## [47,] -0.001008578991 0.012111314 0.00000000 0 0.0096
## [48,] -0.000548506650 0.008538699 0.00000000 0 0.0084
## [49,] -0.000378415808 0.005843082 0.00000000 0 0.0060
## [50,] -0.001179248038 0.013561568 0.00000000 0 0.0144
## [51,] -0.000884918397 0.012109211 0.00000000 0 0.0096
## [52,] -0.000640908862 0.008790442 0.00000000 0 0.0088
## [53,] -0.000481219533 0.007425474 0.00000000 0 0.0056
## [54,] -0.001023386148 0.011652120 0.00000000 0 0.0128
## [55,] -0.000229186273 0.005324289 0.00000000 0 0.0048
## [56,] -0.000044378964 0.002563201 0.00000000 0 0.0032
## [57,] -0.000194187112 0.003984706 0.00000000 0 0.0032
## [58,] -0.000072096773 0.003952996 0.00000000 0 0.0048
## [59,] -0.000222438940 0.006358297 0.00000000 0 0.0064
## [60,] -0.000465856387 0.007311785 0.00000000 0 0.0068
## [61,] -0.000507249524 0.008615512 0.00000000 0 0.0068
## [62,] -0.002010224992 0.017484110 0.00000000 0 0.0196
## [63,] -0.002766052858 0.020736591 0.00000000 0 0.0244
## [64,] -0.000264651539 0.004816263 0.00000000 0 0.0064
## [65,] -0.000347684190 0.005122497 0.00000000 0 0.0056
## [66,] -0.001032462761 0.011133324 0.00000000 0 0.0124
## [67,] -0.001182624247 0.011603311 0.00000000 0 0.0144
## [68,] -0.000372019511 0.006330552 0.00000000 0 0.0064
## [69,] -0.000657901070 0.008531269 0.00000000 0 0.0092
## [70,] -0.001057676500 0.012166526 0.00000000 0 0.0120
## [71,] -0.000475143676 0.006845651 0.00000000 0 0.0060
## [72,] -0.000439326569 0.006753164 0.00000000 0 0.0068
## [73,] -0.000092949948 0.004185770 0.00000000 0 0.0048
## [74,] -0.001121285608 0.012652721 0.00000000 0 0.0132
## [75,] -0.000163110431 0.005258528 0.00000000 0 0.0040
## [76,] -0.000666583248 0.007824870 0.00000000 0 0.0108
## [77,] -0.001752020000 0.016236983 0.00000000 0 0.0160
## [78,] -0.001495399865 0.015946314 0.00000000 0 0.0140
## [79,] -0.001099754674 0.012928164 0.00000000 0 0.0124
## [80,] -0.000066877006 0.007365214 0.00000000 0 0.0076
## [81,] -0.001516897940 0.015429205 0.00000000 0 0.0172
## [82,] -0.001176673921 0.013441634 0.00000000 0 0.0140
## [83,] -0.000718522373 0.011233008 0.00000000 0 0.0100
## [84,] -0.000616854365 0.011635386 0.00000000 0 0.0100
## [85,] -0.001143846694 0.011883260 0.00000000 0 0.0136
## [86,] -0.000875370694 0.009556649 0.00000000 0 0.0116
## [87,] -0.000750211127 0.011014890 0.00000000 0 0.0100
## [88,] -0.000741614158 0.009264901 0.00000000 0 0.0088
## [89,] -0.000386150919 0.006657330 0.00000000 0 0.0056
## [90,] -0.000204521859 0.009110889 0.00000000 0 0.0068
## [91,] -0.000293247879 0.005765034 0.00000000 0 0.0052
## [92,] -0.000282352304 0.005149325 0.00000000 0 0.0068
## [93,] -0.001138716852 0.011304737 0.00000000 0 0.0152
## [94,] -0.001266011357 0.011942801 0.00000000 0 0.0156
## [95,] -0.000397613945 0.005508615 0.00000000 0 0.0088
## [96,] 0.000087079693 0.013488916 0.00000000 0 0.0048
## [97,] -0.000283324406 0.008754581 0.00000000 0 0.0084
## [98,] -0.000244261037 0.007720834 0.00000000 0 0.0064
## [99,] -0.000433145631 0.006846121 0.00000000 0 0.0052
## [100,] -0.000580887863 0.011527986 0.00000000 0 0.0100
## [101,] -0.000950631524 0.011609665 0.00000000 0 0.0104
## [102,] -0.000276464930 0.009732937 0.00000000 0 0.0064
## [103,] -0.000771413255 0.009548917 0.00000000 0 0.0116
## [104,] -0.000154302220 0.003630637 0.00000000 0 0.0044
## [105,] -0.000187755298 0.004938637 0.00000000 0 0.0032
## [106,] -0.000589043759 0.008493988 0.00000000 0 0.0068
## [107,] -0.000463323534 0.007080863 0.00000000 0 0.0064
## [108,] -0.000834812997 0.010219080 0.00000000 0 0.0096
## [109,] -0.000240057116 0.006519918 0.00000000 0 0.0048
## [110,] -0.001213796269 0.012604336 0.00000000 0 0.0128
## [111,] -0.000540787002 0.008119992 0.00000000 0 0.0096
## [112,] -0.000343575048 0.005591067 0.00000000 0 0.0060
## [113,] -0.000778985472 0.009081388 0.00000000 0 0.0100
## [114,] 0.000302931124 0.012134740 0.00000000 0 0.0052
## [115,] -0.000736181526 0.011256503 0.00000000 0 0.0100
## [116,] -0.000845135715 0.010682288 0.00000000 0 0.0100
## [117,] -0.001176187893 0.014308958 0.00000000 0 0.0112
## [118,] -0.001635107136 0.018685322 0.00000000 0 0.0136
## [119,] -0.000705353961 0.009970485 0.00000000 0 0.0092
## [120,] -0.000956057522 0.012182396 0.00000000 0 0.0108
## [121,] -0.000346680507 0.007338784 0.00000000 0 0.0084
## [122,] -0.000834373482 0.009856706 0.00000000 0 0.0116
## [123,] -0.000355320381 0.006853749 0.00000000 0 0.0060
## [124,] -0.001117229635 0.012249560 0.00000000 0 0.0116
## [125,] 0.000042347968 0.007653013 0.00000000 0 0.0036
## [126,] -0.000317663223 0.008373776 0.00000000 0 0.0060
## [127,] -0.000553318610 0.007880219 0.00000000 0 0.0088
## [128,] -0.000469732137 0.010146412 0.00000000 0 0.0084
## [129,] -0.000838411642 0.008752937 0.00000000 0 0.0124
## [130,] -0.000395586737 0.008069839 0.00000000 0 0.0072
## [131,] -0.002709334721 0.022138944 0.00000000 0 0.0208
## [132,] -0.002962443558 0.022495935 0.00000000 0 0.0252
## [133,] -0.001203005725 0.014461196 0.00000000 0 0.0100
## [134,] -0.000532823026 0.007880343 0.00000000 0 0.0084
## [135,] -0.002152094701 0.018434504 0.00000000 0 0.0188
## [136,] -0.001023367549 0.011138389 0.00000000 0 0.0140
## [137,] -0.000668625660 0.007937444 0.00000000 0 0.0108
## [138,] -0.000966608270 0.011678858 0.00000000 0 0.0108
## [139,] -0.000495813868 0.007620320 0.00000000 0 0.0072
## [140,] -0.000616136229 0.008322468 0.00000000 0 0.0068
## [141,] -0.000559038092 0.008101018 0.00000000 0 0.0072
## [142,] -0.000878568545 0.011335108 0.00000000 0 0.0112
## [143,] -0.001088747754 0.012223008 0.00000000 0 0.0108
## [144,] -0.000633849657 0.008418216 0.00000000 0 0.0084
## [145,] -0.000980681727 0.011801631 0.00000000 0 0.0100
## [146,] -0.000151467778 0.006118941 0.00000000 0 0.0068
## [147,] -0.000164166782 0.004424244 0.00000000 0 0.0064
## [148,] -0.000604537236 0.008130696 0.00000000 0 0.0128
## [149,] -0.000269722103 0.010486138 0.00000000 0 0.0080
## [150,] -0.000549261856 0.009858245 0.00000000 0 0.0056
## [151,] -0.000195473236 0.010126083 0.00000000 0 0.0064
## [152,] -0.000702178095 0.009193287 0.00000000 0 0.0080
## [153,] -0.000437215032 0.006843770 0.00000000 0 0.0056
## [154,] -0.000447166647 0.007690697 0.00000000 0 0.0076
## [155,] -0.003238349245 0.021462852 -0.04990976 0 0.0288
## [156,] -0.001086064660 0.011925809 0.00000000 0 0.0124
## [157,] -0.000912651883 0.010753528 0.00000000 0 0.0100
## [158,] -0.001591459864 0.015491332 0.00000000 0 0.0152
## [159,] -0.011205322977 0.058432686 -0.19643005 0 0.0556
## [160,] -0.000696814364 0.010872207 0.00000000 0 0.0076
## [161,] -0.001486669392 0.013905783 0.00000000 0 0.0168
## [162,] -0.002140362698 0.017445957 0.00000000 0 0.0208
## [163,] -0.000280651379 0.004821569 0.00000000 0 0.0044
## [164,] -0.000310678207 0.005138752 0.00000000 0 0.0064
## [165,] -0.000954460838 0.011232236 0.00000000 0 0.0116
## [166,] -0.001790815388 0.019756911 0.00000000 0 0.0140
## [167,] -0.000835241633 0.011087229 0.00000000 0 0.0092
## [168,] -0.001339058957 0.014282890 0.00000000 0 0.0112
## [169,] -0.001372088963 0.014869602 0.00000000 0 0.0120
## [170,] -0.000046073019 0.001556375 0.00000000 0 0.0012
## [171,] -0.000160902428 0.003262978 0.00000000 0 0.0028
## [172,] -0.000154574245 0.005560609 0.00000000 0 0.0044
## [173,] -0.000286844514 0.005929387 0.00000000 0 0.0052
## [174,] -0.000046764673 0.002169896 0.00000000 0 0.0032
## [175,] -0.000191914711 0.006183322 0.00000000 0 0.0072
## [176,] -0.000028344376 0.007570389 0.00000000 0 0.0040
## [177,] -0.000049024107 0.005941999 0.00000000 0 0.0040
## [178,] -0.000148221114 0.003296643 0.00000000 0 0.0024
## [179,] -0.000226494441 0.007136060 0.00000000 0 0.0044
## [180,] -0.000173342042 0.003908216 0.00000000 0 0.0036
## [181,] -0.000846752481 0.010112200 0.00000000 0 0.0092
## [182,] -0.000394853745 0.006089181 0.00000000 0 0.0068
## [183,] -0.000290303575 0.004637215 0.00000000 0 0.0080
## [184,] -0.000940893938 0.012133002 0.00000000 0 0.0132
## [185,] -0.001069679500 0.011358509 0.00000000 0 0.0116
## [186,] -0.000682309044 0.009494861 0.00000000 0 0.0080
## [187,] -0.002611660248 0.020965300 0.00000000 0 0.0208
## [188,] -0.000251849135 0.004586055 0.00000000 0 0.0060
## [189,] -0.000424047277 0.006078313 0.00000000 0 0.0056
## [190,] -0.000599008144 0.006507759 0.00000000 0 0.0100
## [191,] -0.000092599868 0.008141939 0.00000000 0 0.0064
## [192,] -0.001550660708 0.016453987 0.00000000 0 0.0148
## [193,] -0.002427598716 0.020134408 0.00000000 0 0.0212
## [194,] -0.000265933322 0.010791372 0.00000000 0 0.0096
## [195,] -0.001159172612 0.015102321 0.00000000 0 0.0124
## [196,] -0.003392018602 0.027235576 0.00000000 0 0.0240
## [197,] -0.000598168782 0.008410615 0.00000000 0 0.0084
## [198,] -0.001596173806 0.019703456 0.00000000 0 0.0160
## [199,] -0.004345241957 0.041853253 0.00000000 0 0.0216
## [200,] -0.000804285267 0.009694092 0.00000000 0 0.0116
## [201,] -0.000629721061 0.016742453 0.00000000 0 0.0100
## [202,] -0.001609756559 0.014727084 0.00000000 0 0.0164
## [203,] -0.002224708528 0.022528658 0.00000000 0 0.0204
## [204,] -0.001264913222 0.015732057 0.00000000 0 0.0136
## [205,] -0.000618481355 0.010879643 0.00000000 0 0.0060
## [206,] -0.001026264696 0.012127034 0.00000000 0 0.0116
## [207,] -0.001275021542 0.014656490 0.00000000 0 0.0124
## [208,] -0.002644942881 0.020778979 0.00000000 0 0.0208
## [209,] -0.000922493356 0.011404384 0.00000000 0 0.0108
## [210,] -0.000772856550 0.010450643 0.00000000 0 0.0100
## [211,] -0.000213112732 0.004547820 0.00000000 0 0.0052
## [212,] -0.000144996776 0.002920611 0.00000000 0 0.0032
## [213,] -0.000985951030 0.011875989 0.00000000 0 0.0112
## [214,] -0.001153393420 0.012441197 0.00000000 0 0.0120
## [215,] -0.000266936163 0.013188477 0.00000000 0 0.0088
## [216,] -0.004213807068 0.027695766 -0.06049490 0 0.0300
## [217,] -0.005249281667 0.030861139 -0.08951090 0 0.0380
## [218,] -0.001343879479 0.015220153 0.00000000 0 0.0148
## [219,] -0.000525460197 0.006917387 0.00000000 0 0.0084
## [220,] -0.003347366025 0.032292219 0.00000000 0 0.0212
## [221,] -0.000342310578 0.014132439 0.00000000 0 0.0080
## [222,] -0.001186662786 0.012954979 0.00000000 0 0.0124
## [223,] 0.000386531762 0.029549778 0.00000000 0 0.0072
## [224,] -0.002928408768 0.026360799 0.00000000 0 0.0212
## [225,] -0.020173348091 0.156453510 -0.12090822 0 0.0352
## [226,] -0.000517891993 0.007233467 0.00000000 0 0.0080
## [227,] -0.000689418633 0.008672940 0.00000000 0 0.0080
## [228,] -0.002637983342 0.032597610 0.00000000 0 0.0136
## [229,] -0.002046657498 0.021509461 0.00000000 0 0.0164
## [230,] -0.000322084823 0.009154093 0.00000000 0 0.0052
## [231,] -0.000295942865 0.009261622 0.00000000 0 0.0076
## [232,] -0.000354192815 0.006482172 0.00000000 0 0.0076
## [233,] -0.001186478955 0.013570417 0.00000000 0 0.0120
## [234,] -0.003566095233 0.032978588 0.00000000 0 0.0244
## [235,] -0.000392045033 0.006462143 0.00000000 0 0.0072
## [236,] -0.000779039679 0.012082526 0.00000000 0 0.0080
## [237,] -0.002155516744 0.019304375 0.00000000 0 0.0192
## [238,] -0.001255211416 0.012615177 0.00000000 0 0.0132
## [239,] -0.000626255037 0.008497253 0.00000000 0 0.0084
## [240,] -0.000840631965 0.011984831 0.00000000 0 0.0080
## [241,] -0.001038160944 0.012258478 0.00000000 0 0.0100
## [242,] -0.000660484873 0.011937862 0.00000000 0 0.0104
## [243,] -0.001271374299 0.013343890 0.00000000 0 0.0140
## [244,] -0.000621447517 0.012683739 0.00000000 0 0.0108
## [245,] -0.001124918295 0.012804914 0.00000000 0 0.0108
## [246,] -0.001255117133 0.013725228 0.00000000 0 0.0124
## [247,] -0.001109979018 0.013805342 0.00000000 0 0.0128
## [248,] -0.001560015760 0.018906536 0.00000000 0 0.0148
## [249,] 0.000393171459 0.030123324 0.00000000 0 0.0080
## [250,] -0.001187165896 0.013675453 0.00000000 0 0.0132
## [251,] -0.000656286524 0.010189798 0.00000000 0 0.0084
## [252,] -0.000904182613 0.018972230 0.00000000 0 0.0100
## [253,] -0.000655325100 0.009787549 0.00000000 0 0.0096
## [254,] -0.001784071051 0.016912946 0.00000000 0 0.0160
## [255,] -0.000553790991 0.009545195 0.00000000 0 0.0104
## [256,] -0.001164427694 0.011810751 0.00000000 0 0.0144
## [257,] -0.001136698546 0.017138432 0.00000000 0 0.0152
## [258,] -0.000882993278 0.011186429 0.00000000 0 0.0096
## [259,] -0.000484531773 0.006726260 0.00000000 0 0.0068
## [260,] -0.000742557807 0.010588809 0.00000000 0 0.0088
## [261,] -0.000614557905 0.013673807 0.00000000 0 0.0116
## [262,] -0.001121191245 0.011256893 0.00000000 0 0.0148
## [263,] -0.000741841411 0.009183923 0.00000000 0 0.0096
## [264,] -0.000893035976 0.010846160 0.00000000 0 0.0116
## [265,] -0.000671366657 0.007551771 0.00000000 0 0.0104
## [266,] -0.000955683337 0.011558628 0.00000000 0 0.0112
## [267,] -0.000937620393 0.011619687 0.00000000 0 0.0108
## [268,] -0.000757380135 0.009336852 0.00000000 0 0.0100
## [269,] -0.000694611902 0.009414837 0.00000000 0 0.0084
## [270,] -0.000573465620 0.013267771 0.00000000 0 0.0072
## [271,] -0.000917967040 0.011284317 0.00000000 0 0.0108
## [272,] -0.000511043584 0.008155041 0.00000000 0 0.0076
## [273,] -0.001358118596 0.015762146 0.00000000 0 0.0128
## [274,] -0.001811537264 0.016479492 0.00000000 0 0.0164
## [275,] -0.000568108532 0.012610049 0.00000000 0 0.0080
## [276,] -0.000440134959 0.009197715 0.00000000 0 0.0060
## [277,] -0.000973323927 0.011663662 0.00000000 0 0.0120
## [278,] -0.000961177394 0.013728111 0.00000000 0 0.0092
## [279,] -0.001423229484 0.015252276 0.00000000 0 0.0128
## [280,] -0.002181678645 0.018309022 0.00000000 0 0.0188
## [281,] -0.002673531063 0.024700950 0.00000000 0 0.0192
## [282,] -0.001063234077 0.013805015 0.00000000 0 0.0096
## [283,] -0.001510663121 0.014638525 0.00000000 0 0.0164
## [284,] -0.000891186794 0.010860139 0.00000000 0 0.0100
## [285,] -0.002515848348 0.022724352 0.00000000 0 0.0188
## [286,] -0.000772775153 0.010449043 0.00000000 0 0.0108
## [287,] -0.001513709716 0.013767728 0.00000000 0 0.0160
## [288,] -0.003653966825 0.025328827 -0.04856228 0 0.0284
## [289,] -0.000372721172 0.007277194 0.00000000 0 0.0076
## [290,] -0.000698858519 0.009855018 0.00000000 0 0.0080
## [291,] -0.001030578898 0.012283469 0.00000000 0 0.0124
## [292,] -0.000685053296 0.011818040 0.00000000 0 0.0096
## [293,] 0.000392752100 0.035575731 0.00000000 0 0.0096
## [294,] -0.000909640656 0.010735756 0.00000000 0 0.0096
## [295,] -0.000381870445 0.008728064 0.00000000 0 0.0076
## [296,] -0.000829584657 0.010342030 0.00000000 0 0.0092
## [297,] -0.000338730998 0.015516661 0.00000000 0 0.0100
## [298,] -0.000518517642 0.006616986 0.00000000 0 0.0092
## [299,] -0.001317215104 0.016965853 0.00000000 0 0.0108
## [300,] -0.000948878805 0.014451147 0.00000000 0 0.0104
## [301,] -0.000587552287 0.011994165 0.00000000 0 0.0084
## [302,] -0.000655286933 0.009113009 0.00000000 0 0.0080
## [303,] -0.000468847452 0.017930685 0.00000000 0 0.0124
## [304,] -0.001208774136 0.013379842 0.00000000 0 0.0136
## [305,] -0.001786183593 0.028053728 0.00000000 0 0.0140
## [306,] -0.001785152660 0.017476191 0.00000000 0 0.0148
## [307,] -0.000562037153 0.007074092 0.00000000 0 0.0100
## [308,] -0.000786816287 0.011239889 0.00000000 0 0.0104
## [309,] -0.001340298800 0.014314740 0.00000000 0 0.0120
## [310,] -0.000759817304 0.009060032 0.00000000 0 0.0100
## [311,] -0.000738070839 0.008356797 0.00000000 0 0.0104
## [312,] -0.000532001796 0.007879454 0.00000000 0 0.0076
## [313,] -0.000486685886 0.007731110 0.00000000 0 0.0064
## [314,] -0.000647234708 0.019692672 0.00000000 0 0.0112
## [315,] -0.001773896466 0.022662443 0.00000000 0 0.0156
## [316,] -0.001126977680 0.012694563 0.00000000 0 0.0104
## [317,] -0.000696548466 0.010333777 0.00000000 0 0.0080
## [318,] -0.003056768756 0.057753302 0.00000000 0 0.0136
## [319,] -0.000710299148 0.010698338 0.00000000 0 0.0080
## [320,] -0.001653376619 0.016470235 0.00000000 0 0.0152
## [321,] -0.002101892467 0.020074655 0.00000000 0 0.0176
## [322,] -0.001054878151 0.012527532 0.00000000 0 0.0124
## [323,] -0.000587843828 0.009555083 0.00000000 0 0.0088
## [324,] -0.001029234548 0.014518356 0.00000000 0 0.0104
## [325,] -0.001363062799 0.017523169 0.00000000 0 0.0152
## [326,] -0.000741272618 0.009691118 0.00000000 0 0.0076
## [327,] -0.000371752855 0.006545548 0.00000000 0 0.0056
## [328,] -0.000335487314 0.006620201 0.00000000 0 0.0060
## [329,] -0.000629874236 0.012111380 0.00000000 0 0.0092
## [330,] -0.000557132243 0.009422738 0.00000000 0 0.0084
## [331,] -0.000659746325 0.008853469 0.00000000 0 0.0104
## [332,] -0.000816478742 0.009453646 0.00000000 0 0.0100
## [333,] -0.000622634524 0.009131892 0.00000000 0 0.0084
## [334,] -0.000458163006 0.007131570 0.00000000 0 0.0076
## [335,] -0.002149698239 0.016392265 0.00000000 0 0.0212
## [336,] -0.001345687486 0.013902186 0.00000000 0 0.0136
## [337,] -0.000476604973 0.008706755 0.00000000 0 0.0076
## [338,] -0.000677007160 0.019093359 0.00000000 0 0.0104
## [339,] -0.001095821878 0.012436456 0.00000000 0 0.0136
## [340,] -0.001182653857 0.012167904 0.00000000 0 0.0120
## [341,] -0.001643118805 0.016998549 0.00000000 0 0.0148
## [342,] -0.001431085353 0.016726551 0.00000000 0 0.0128
## [343,] -0.000451826624 0.007402079 0.00000000 0 0.0052
## [344,] -0.001067014707 0.012876105 0.00000000 0 0.0116
## [345,] -0.001061833237 0.012776061 0.00000000 0 0.0116
## [346,] -0.000866683520 0.012532638 0.00000000 0 0.0112
## [347,] -0.000758525431 0.008715685 0.00000000 0 0.0116
## [348,] -0.001160989504 0.012666400 0.00000000 0 0.0112
## [349,] -0.000598135060 0.008508540 0.00000000 0 0.0088
## [350,] -0.000907854303 0.011391831 0.00000000 0 0.0092
## [351,] 0.000170623076 0.017807681 0.00000000 0 0.0052
## [352,] -0.000634929018 0.009706921 0.00000000 0 0.0056
## [353,] -0.000385993714 0.018435190 0.00000000 0 0.0096
## [354,] -0.001631088960 0.018511951 0.00000000 0 0.0108
## [355,] -0.000551227602 0.007007380 0.00000000 0 0.0080
## [356,] -0.001009253895 0.011014035 0.00000000 0 0.0124
## [357,] -0.000498831368 0.007346799 0.00000000 0 0.0068
## [358,] -0.000799020959 0.009662662 0.00000000 0 0.0092
## [359,] -0.004868833217 0.031810955 -0.07730338 0 0.0336
## [360,] -0.001173920955 0.015936589 0.00000000 0 0.0100
## [361,] -0.000180756926 0.005287726 0.00000000 0 0.0064
## [362,] -0.000883400418 0.011932091 0.00000000 0 0.0096
## [363,] -0.000836374042 0.013079605 0.00000000 0 0.0096
## [364,] -0.000301205387 0.007890105 0.00000000 0 0.0068
## [365,] -0.000937875636 0.012520621 0.00000000 0 0.0116
## [366,] -0.001371679724 0.013846423 0.00000000 0 0.0160
## [367,] -0.000699368354 0.011008155 0.00000000 0 0.0080
## [368,] -0.001349127591 0.015394943 0.00000000 0 0.0124
## [369,] -0.000422207456 0.006980487 0.00000000 0 0.0052
## [370,] -0.000913098003 0.012933966 0.00000000 0 0.0100
## [371,] -0.000866904589 0.011086107 0.00000000 0 0.0104
## [372,] -0.000845381375 0.013341710 0.00000000 0 0.0104
## [373,] 0.000009225180 0.014829017 0.00000000 0 0.0080
## [374,] -0.001911330368 0.019403328 0.00000000 0 0.0156
## [375,] -0.000280616790 0.005730011 0.00000000 0 0.0052
## [376,] -0.000274757716 0.006509277 0.00000000 0 0.0052
## [377,] -0.000684440709 0.009985014 0.00000000 0 0.0096
## [378,] -0.000949219936 0.013860559 0.00000000 0 0.0128
## [379,] -0.000088130129 0.006777186 0.00000000 0 0.0056
## [380,] -0.000594632954 0.008536899 0.00000000 0 0.0104
## [381,] -0.000711084167 0.010823656 0.00000000 0 0.0092
## [382,] -0.000352505853 0.006154795 0.00000000 0 0.0048
## [383,] -0.004238786513 0.028890037 -0.05332451 0 0.0308
## [384,] -0.002847488909 0.021112427 0.00000000 0 0.0236
## [385,] -0.000308661799 0.007133392 0.00000000 0 0.0072
## [386,] -0.001192610687 0.015831016 0.00000000 0 0.0104
## [387,] -0.000811874658 0.010554523 0.00000000 0 0.0092
## [388,] -0.000793541428 0.010661863 0.00000000 0 0.0100
## [389,] -0.000851876180 0.010330571 0.00000000 0 0.0100
## [390,] -0.001123946741 0.018408654 0.00000000 0 0.0120
## [391,] -0.000166401400 0.011016338 0.00000000 0 0.0068
## [392,] -0.000315882171 0.018796607 0.00000000 0 0.0104
## [393,] -0.001143732861 0.016467974 0.00000000 0 0.0128
## [394,] -0.000856451844 0.011384545 0.00000000 0 0.0092
## [395,] -0.000727338678 0.009594630 0.00000000 0 0.0092
## [396,] -0.000909056530 0.011840926 0.00000000 0 0.0092
## [397,] -0.001133260171 0.014292886 0.00000000 0 0.0116
## [398,] -0.000662892884 0.009984557 0.00000000 0 0.0080
## [399,] -0.000161078800 0.003865647 0.00000000 0 0.0040
## [400,] -0.000253661182 0.008367009 0.00000000 0 0.0076
## [401,] -0.001269329794 0.014244370 0.00000000 0 0.0128
## [402,] -0.000673364970 0.015895636 0.00000000 0 0.0088
## [403,] -0.000306495738 0.004891275 0.00000000 0 0.0048
## [404,] -0.000494390977 0.008219618 0.00000000 0 0.0080
## [405,] -0.000622873529 0.008663521 0.00000000 0 0.0084
## [406,] -0.000818887277 0.010799494 0.00000000 0 0.0088
## [407,] -0.000184860779 0.005248432 0.00000000 0 0.0060
## [408,] -0.000902356254 0.011931967 0.00000000 0 0.0100
## [409,] -0.001164626888 0.011800629 0.00000000 0 0.0144
## [410,] 0.000290932809 0.023068998 0.00000000 0 0.0076
## [411,] -0.002517533563 0.026099454 0.00000000 0 0.0204
## [412,] -0.001022323182 0.012265226 0.00000000 0 0.0104
## [413,] -0.000850913069 0.010834061 0.00000000 0 0.0092
## [414,] -0.002072362398 0.032065527 0.00000000 0 0.0136
## [415,] -0.000660840530 0.008109137 0.00000000 0 0.0100
## [416,] -0.001225348983 0.014776159 0.00000000 0 0.0112
## [417,] -0.000790251471 0.010084110 0.00000000 0 0.0092
## [418,] -0.001315051722 0.016017294 0.00000000 0 0.0112
## [419,] -0.000721272228 0.010791744 0.00000000 0 0.0124
## [420,] -0.001099593834 0.016353753 0.00000000 0 0.0124
## [421,] -0.000206141360 0.011165376 0.00000000 0 0.0080
## [422,] -0.002098567373 0.021727789 0.00000000 0 0.0200
## [423,] -0.001304820361 0.013350790 0.00000000 0 0.0132
## [424,] -0.000921733765 0.010682091 0.00000000 0 0.0100
## [425,] -0.000454651585 0.009592666 0.00000000 0 0.0088
## [426,] -0.000814689237 0.010869347 0.00000000 0 0.0084
## [427,] -0.000673847766 0.008654984 0.00000000 0 0.0092
## [428,] -0.000832158700 0.009861346 0.00000000 0 0.0116
## [429,] -0.001809126871 0.019152633 0.00000000 0 0.0152
## [430,] -0.000433693319 0.006570902 0.00000000 0 0.0084
## [431,] -0.000524745819 0.007668248 0.00000000 0 0.0088
## [432,] -0.000537980791 0.006822000 0.00000000 0 0.0088
## [433,] -0.000922460814 0.011099129 0.00000000 0 0.0112
## [434,] -0.000885180102 0.011722129 0.00000000 0 0.0132
## [435,] -0.001247990886 0.015928720 0.00000000 0 0.0112
## [436,] -0.001469002642 0.015489438 0.00000000 0 0.0136
## [437,] -0.000697821225 0.009699172 0.00000000 0 0.0088
## [438,] -0.001090351119 0.040066382 0.00000000 0 0.0096
## [439,] -0.001065871740 0.013921605 0.00000000 0 0.0112
## [440,] -0.002574823108 0.024906087 0.00000000 0 0.0192
## [441,] -0.001055358921 0.012687094 0.00000000 0 0.0112
## [442,] -0.001776004382 0.018182615 0.00000000 0 0.0152
## [443,] -0.000273166587 0.004249787 0.00000000 0 0.0052
## [444,] -0.000820156150 0.011100346 0.00000000 0 0.0104
## [445,] -0.000580038700 0.011827554 0.00000000 0 0.0100
## [446,] -0.002460848469 0.028356332 0.00000000 0 0.0176
## [447,] -0.001458412860 0.015563502 0.00000000 0 0.0124
## [448,] -0.000864341100 0.010431620 0.00000000 0 0.0100
## [449,] -0.000909404857 0.011193560 0.00000000 0 0.0112
## [450,] -0.000870683814 0.011281937 0.00000000 0 0.0096
## [451,] -0.001033992518 0.011495264 0.00000000 0 0.0104
## [452,] -0.000431473173 0.008451466 0.00000000 0 0.0088
## [453,] -0.001182335207 0.012008487 0.00000000 0 0.0160
## [454,] -0.000705524066 0.008871108 0.00000000 0 0.0092
## [455,] -0.000467131766 0.008778366 0.00000000 0 0.0096
## [456,] -0.000945736870 0.012460361 0.00000000 0 0.0116
## [457,] -0.000823854039 0.009644721 0.00000000 0 0.0116
## [458,] -0.002105797905 0.029524799 0.00000000 0 0.0132
## [459,] -0.000905536658 0.011424234 0.00000000 0 0.0096
## [460,] -0.000387418598 0.007404070 0.00000000 0 0.0056
## [461,] -0.001337522456 0.014393228 0.00000000 0 0.0124
## [462,] -0.001056759917 0.022784407 0.00000000 0 0.0116
## [463,] -0.000416190443 0.009354754 0.00000000 0 0.0088
## [464,] -0.001066882754 0.010975703 0.00000000 0 0.0140
## [465,] -0.001787888681 0.016925769 0.00000000 0 0.0148
## [466,] -0.001045765178 0.012469994 0.00000000 0 0.0124
## [467,] -0.001808342107 0.017058895 0.00000000 0 0.0192
## [468,] -0.001978547626 0.019344890 0.00000000 0 0.0160
## [469,] -0.000796748212 0.009574441 0.00000000 0 0.0096
## [470,] -0.000603424715 0.008626602 0.00000000 0 0.0084
## [471,] -0.001810293108 0.020256469 0.00000000 0 0.0144
## [472,] -0.000760145823 0.008606127 0.00000000 0 0.0108
## [473,] -0.001325535007 0.014115314 0.00000000 0 0.0128
## [474,] -0.002069485649 0.022174201 0.00000000 0 0.0168
## [475,] -0.000663606593 0.008152174 0.00000000 0 0.0080
## [476,] -0.000903481561 0.011615899 0.00000000 0 0.0088
## [477,] -0.001146107338 0.014220059 0.00000000 0 0.0136
## [478,] -0.003714243994 0.028174286 -0.02141816 0 0.0280
## [479,] -0.000694909181 0.008589169 0.00000000 0 0.0088
## [480,] -0.000847850923 0.009925412 0.00000000 0 0.0112
## [481,] -0.001081579123 0.011627612 0.00000000 0 0.0108
## [482,] -0.000701817985 0.009426951 0.00000000 0 0.0092
## [483,] -0.001310666423 0.016478602 0.00000000 0 0.0120
## [484,] -0.000095673437 0.018931018 0.00000000 0 0.0064
## [485,] -0.002513919275 0.024036145 0.00000000 0 0.0176
## [486,] -0.000714618021 0.010693836 0.00000000 0 0.0092
## [487,] 0.000293911216 0.024734645 0.00000000 0 0.0044
## [488,] -0.001024391233 0.012635028 0.00000000 0 0.0096
## [489,] -0.002066495901 0.020255915 0.00000000 0 0.0184
## [490,] -0.001177809959 0.013037992 0.00000000 0 0.0132
## [491,] -0.001220692628 0.014710536 0.00000000 0 0.0108
## [492,] -0.001703387205 0.016755934 0.00000000 0 0.0160
## [493,] -0.000702220473 0.010405005 0.00000000 0 0.0100
## [494,] -0.000557977449 0.011732295 0.00000000 0 0.0072
## [495,] -0.001331713086 0.015729311 0.00000000 0 0.0112
## [496,] -0.001275963739 0.013395032 0.00000000 0 0.0116
## [497,] -0.000840571692 0.017253737 0.00000000 0 0.0120
## [498,] -0.001159554206 0.014589274 0.00000000 0 0.0116
## [499,] -0.000558606319 0.007335529 0.00000000 0 0.0080
## [500,] -0.001361832333 0.012945146 0.00000000 0 0.0152
## [501,] -0.002301646445 0.021125463 0.00000000 0 0.0176
## [502,] -0.004799247267 0.033788022 -0.05912012 0 0.0324
## [503,] -0.000748444498 0.009215419 0.00000000 0 0.0120
## [504,] -0.006288226022 0.034013739 -0.11868835 0 0.0424
## [505,] -0.002516701387 0.023177473 0.00000000 0 0.0212
## [506,] -0.000889277346 0.011896885 0.00000000 0 0.0124
## [507,] -0.000558417744 0.021611387 0.00000000 0 0.0104
## [508,] -0.001282436994 0.014694072 0.00000000 0 0.0136
## [509,] -0.002202550787 0.020807719 0.00000000 0 0.0172
## [510,] -0.003815130459 0.065851278 0.00000000 0 0.0160
## [511,] -0.000450630374 0.009801785 0.00000000 0 0.0072
## [512,] -0.000738166366 0.009830656 0.00000000 0 0.0084
## [513,] -0.001936506898 0.020192717 0.00000000 0 0.0156
## [514,] -0.000797321198 0.011677112 0.00000000 0 0.0108
## [515,] -0.000560361380 0.008502790 0.00000000 0 0.0092
## [516,] -0.001540996179 0.016337600 0.00000000 0 0.0144
## [517,] -0.002354014771 0.022085179 0.00000000 0 0.0192
## [518,] -0.000185525538 0.018298939 0.00000000 0 0.0064
## [519,] -0.001260143952 0.012593858 0.00000000 0 0.0140
## [520,] -0.001037709638 0.011238347 0.00000000 0 0.0104
## [521,] -0.002103514177 0.040226554 0.00000000 0 0.0132
## [522,] -0.000765533546 0.011105289 0.00000000 0 0.0072
## [523,] -0.001701402050 0.014821152 0.00000000 0 0.0180
## [524,] -0.003901715556 0.027307111 -0.04586726 0 0.0300
## [525,] -0.001426918856 0.014030567 0.00000000 0 0.0132
## [526,] -0.002371332403 0.020118757 0.00000000 0 0.0200
## [527,] -0.000858208566 0.009938438 0.00000000 0 0.0104
## [528,] -0.000778052423 0.010843947 0.00000000 0 0.0092
## [529,] -0.001379554261 0.014250732 0.00000000 0 0.0140
## [530,] -0.000261019648 0.021980693 0.00000000 0 0.0104
## [531,] -0.000932992153 0.017158412 0.00000000 0 0.0144
## [532,] -0.001071924522 0.012829936 0.00000000 0 0.0092
## [533,] -0.002602051900 0.023298605 0.00000000 0 0.0212
## [534,] -0.003358744695 0.059252787 0.00000000 0 0.0156
## [535,] -0.000816480437 0.010190205 0.00000000 0 0.0080
## [536,] -0.000313896899 0.024806237 0.00000000 0 0.0080
## [537,] -0.002858744729 0.023377719 0.00000000 0 0.0228
## [538,] -0.002806381183 0.023046451 0.00000000 0 0.0204
## [539,] -0.000827845732 0.012616610 0.00000000 0 0.0092
## [540,] -0.001390230809 0.014993866 0.00000000 0 0.0136
## [541,] -0.001961347922 0.017111743 0.00000000 0 0.0180
## [542,] -0.000876292473 0.018788566 0.00000000 0 0.0116
## [543,] -0.001367868988 0.014226749 0.00000000 0 0.0140
## [544,] -0.004011499971 0.033148373 0.00000000 0 0.0244
## [545,] -0.002929618555 0.026934991 0.00000000 0 0.0200
## [546,] -0.001081594485 0.012605509 0.00000000 0 0.0132
## [547,] -0.002654969262 0.021903333 0.00000000 0 0.0252
## [548,] -0.002715179096 0.020971956 0.00000000 0 0.0212
## [549,] -0.001198256304 0.017016433 0.00000000 0 0.0136
## [550,] -0.001744314876 0.017641266 0.00000000 0 0.0144
## [551,] -0.000321507667 0.007001099 0.00000000 0 0.0060
## [552,] -0.003211307509 0.025216325 0.00000000 0 0.0240
## [553,] -0.001819611307 0.016803011 0.00000000 0 0.0204
## [554,] -0.001147897155 0.012526218 0.00000000 0 0.0120
## [555,] -0.000443507752 0.015402845 0.00000000 0 0.0088
## [556,] -0.001077368049 0.012470528 0.00000000 0 0.0108
## [557,] -0.001030969669 0.013552104 0.00000000 0 0.0116
## [558,] -0.001759724870 0.032956237 0.00000000 0 0.0096
## [559,] -0.000483469314 0.008224478 0.00000000 0 0.0068
## [560,] -0.000817124746 0.011430166 0.00000000 0 0.0068
## [561,] -0.002499698371 0.024787223 0.00000000 0 0.0196
## [562,] -0.000761113444 0.010817446 0.00000000 0 0.0072
## [563,] -0.001351464297 0.016176986 0.00000000 0 0.0120
## [564,] -0.000792379139 0.011385051 0.00000000 0 0.0108
## [565,] -0.001511233216 0.017234270 0.00000000 0 0.0128
## [566,] -0.000985536798 0.011890582 0.00000000 0 0.0104
## [567,] -0.001514995980 0.019698414 0.00000000 0 0.0108
## [568,] -0.000784102125 0.009825488 0.00000000 0 0.0092
## [569,] -0.001111623518 0.013990311 0.00000000 0 0.0108
## [570,] -0.000838932196 0.022068366 0.00000000 0 0.0120
## [571,] -0.000772167022 0.010567922 0.00000000 0 0.0088
## [572,] -0.000925033438 0.010140514 0.00000000 0 0.0132
## [573,] -0.001720551496 0.015739949 0.00000000 0 0.0160
## [574,] -0.001828174842 0.016880108 0.00000000 0 0.0176
## [575,] -0.000896729260 0.011836839 0.00000000 0 0.0104
## [576,] -0.001232049794 0.012530837 0.00000000 0 0.0120
## [577,] -0.001713802851 0.017275499 0.00000000 0 0.0152
## [578,] -0.001584481425 0.015988393 0.00000000 0 0.0148
## [579,] -0.000841557679 0.010757122 0.00000000 0 0.0100
## [580,] -0.000535540306 0.006621653 0.00000000 0 0.0092
## [581,] -0.002684828932 0.025645459 0.00000000 0 0.0184
## [582,] -0.000970050551 0.011801142 0.00000000 0 0.0100
## [583,] -0.000575391884 0.008962500 0.00000000 0 0.0092
## [584,] -0.001277469875 0.017611904 0.00000000 0 0.0120
## [585,] -0.003249180320 0.032134346 0.00000000 0 0.0216
## [586,] -0.000868206528 0.011077124 0.00000000 0 0.0124
## [587,] -0.001047120561 0.012617718 0.00000000 0 0.0092
## [588,] -0.000849437370 0.012258413 0.00000000 0 0.0092
## [589,] -0.002576938446 0.021942021 0.00000000 0 0.0200
## [590,] -0.000766092753 0.010511929 0.00000000 0 0.0112
## [591,] -0.000806342282 0.010287107 0.00000000 0 0.0096
## [592,] -0.000790504621 0.009676200 0.00000000 0 0.0104
## [593,] -0.001705982426 0.017222286 0.00000000 0 0.0156
## [594,] -0.001814351938 0.020034140 0.00000000 0 0.0148
## [595,] -0.001086221070 0.011100966 0.00000000 0 0.0136
## [596,] -0.000490645582 0.006699115 0.00000000 0 0.0076
## [597,] -0.003858049531 0.032742077 0.00000000 0 0.0228
## [598,] -0.002238752957 0.018415889 0.00000000 0 0.0204
## [599,] -0.000707416354 0.012984304 0.00000000 0 0.0080
## [600,] -0.002126280827 0.017963663 0.00000000 0 0.0200
## [601,] -0.001532635573 0.015291233 0.00000000 0 0.0152
## [602,] -0.000954199632 0.013595414 0.00000000 0 0.0092
## [603,] -0.000704995630 0.009715644 0.00000000 0 0.0108
## [604,] -0.001660404449 0.016752035 0.00000000 0 0.0156
## [605,] -0.000374041618 0.008825640 0.00000000 0 0.0088
## [606,] -0.001413006959 0.025662920 0.00000000 0 0.0108
## [607,] 0.000386092152 0.023953922 0.00000000 0 0.0084
## [608,] -0.000537746421 0.007704036 0.00000000 0 0.0064
## [609,] -0.001438324819 0.015404619 0.00000000 0 0.0140
## [610,] -0.000617746195 0.008165568 0.00000000 0 0.0100
## [611,] -0.000880857035 0.010466872 0.00000000 0 0.0092
## [612,] -0.000571764021 0.008127769 0.00000000 0 0.0084
## [613,] -0.001156237762 0.011897470 0.00000000 0 0.0136
## [614,] -0.000807315152 0.010034944 0.00000000 0 0.0096
## [615,] -0.000912287447 0.011501060 0.00000000 0 0.0100
## [616,] -0.000514392498 0.007278279 0.00000000 0 0.0076
## [617,] -0.001726120721 0.019517495 0.00000000 0 0.0164
## [618,] -0.000799046814 0.011730642 0.00000000 0 0.0080
## [619,] -0.001256839343 0.011586832 0.00000000 0 0.0148
## [620,] -0.000363197568 0.006362618 0.00000000 0 0.0080
## [621,] -0.000963594095 0.013202593 0.00000000 0 0.0112
## [622,] -0.001190645436 0.012741106 0.00000000 0 0.0128
## [623,] -0.000450509879 0.010188536 0.00000000 0 0.0072
## [624,] -0.002440603872 0.020433566 0.00000000 0 0.0204
## [625,] -0.002093768462 0.019700447 0.00000000 0 0.0180
## [626,] -0.001268629928 0.014018842 0.00000000 0 0.0124
## [627,] -0.000483179399 0.007244052 0.00000000 0 0.0060
## [628,] -0.000919775236 0.013172804 0.00000000 0 0.0124
## [629,] -0.000609287378 0.011068640 0.00000000 0 0.0072
## [630,] -0.001178071331 0.013224623 0.00000000 0 0.0108
## [631,] -0.000639882736 0.010127778 0.00000000 0 0.0096
## [632,] -0.000920448358 0.011733652 0.00000000 0 0.0108
## [633,] -0.001425429991 0.016710647 0.00000000 0 0.0148
## [634,] -0.000863141052 0.012597563 0.00000000 0 0.0100
## [635,] -0.001329900434 0.013962215 0.00000000 0 0.0140
## [636,] -0.001779362346 0.019229715 0.00000000 0 0.0172
## [637,] -0.002009985451 0.021885448 0.00000000 0 0.0152
## [638,] -0.000588283445 0.008034087 0.00000000 0 0.0088
## [639,] -0.001564336486 0.018729597 0.00000000 0 0.0140
## [640,] -0.000718906334 0.008339499 0.00000000 0 0.0100
## [641,] -0.001757729430 0.019993950 0.00000000 0 0.0148
## [642,] -0.001005875018 0.011951154 0.00000000 0 0.0120
## [643,] -0.001417063600 0.014078560 0.00000000 0 0.0160
## [644,] -0.001820325327 0.016826487 0.00000000 0 0.0180
## [645,] -0.002644775156 0.022488744 0.00000000 0 0.0216
## [646,] -0.003031699589 0.024276112 0.00000000 0 0.0220
## [647,] -0.000629336097 0.009066464 0.00000000 0 0.0088
## [648,] -0.001648728944 0.015258437 0.00000000 0 0.0164
## [649,] -0.002108373889 0.019920762 0.00000000 0 0.0156
## [650,] -0.001545951474 0.013911093 0.00000000 0 0.0164
## [651,] -0.000953268125 0.012534074 0.00000000 0 0.0100
## [652,] -0.000717691981 0.015177087 0.00000000 0 0.0116
## [653,] -0.000761395094 0.010224604 0.00000000 0 0.0092
## [654,] -0.000963111741 0.012128174 0.00000000 0 0.0112
## [655,] -0.000527329228 0.007770202 0.00000000 0 0.0084
## [656,] -0.000420030057 0.010349193 0.00000000 0 0.0084
## [657,] -0.002948874966 0.028209621 0.00000000 0 0.0196
## [658,] 0.000370056242 0.023222474 0.00000000 0 0.0084
## [659,] -0.001149045079 0.015567084 0.00000000 0 0.0124
## [660,] -0.000645965780 0.007931202 0.00000000 0 0.0092
## [661,] -0.000953618339 0.011966187 0.00000000 0 0.0128
## [662,] -0.000633722618 0.011166534 0.00000000 0 0.0084
## [663,] -0.001834698393 0.016063532 0.00000000 0 0.0172
## [664,] -0.000500243685 0.009375228 0.00000000 0 0.0080
## [665,] -0.001868028735 0.025428884 0.00000000 0 0.0172
## [666,] -0.000905886167 0.010886668 0.00000000 0 0.0120
## [667,] -0.000800623373 0.011099380 0.00000000 0 0.0096
## [668,] -0.000771397926 0.010000676 0.00000000 0 0.0088
## [669,] -0.001396403587 0.016489083 0.00000000 0 0.0124
## [670,] -0.001655279929 0.015792704 0.00000000 0 0.0164
Because race/ethnicity might be on the causal pathway (mediator), we want to see if anything shows up when we exclude those variables from the model
priors.npb <- priors.npb.24
#' Exposures
colnames(X.scaled)
## [1] "mean_pm" "mean_o3" "mean_temp"
## [4] "pct_tree_cover" "pct_impervious" "mean_aadt_intensity"
## [7] "dist_m_tri" "dist_m_npl" "dist_m_waste_site"
## [10] "dist_m_major_emit" "dist_m_cafo" "dist_m_mine_well"
## [13] "cvd_rate_adj" "res_rate_adj" "violent_crime_rate"
## [16] "property_crime_rate" "pct_less_hs" "pct_unemp"
## [19] "pct_limited_eng" "pct_hh_pov" "pct_poc"
#' Covariates
colnames(W.scaled2)
## [1] "lat" "lon" "lat_lon_int" "latina_re"
## [5] "black_re" "other_re" "ed_no_hs" "ed_hs"
## [9] "ed_aa" "ed_4yr" "low_bmi" "ovwt_bmi"
## [13] "obese_bmi" "concep_spring" "concep_summer" "concep_fall"
## [17] "concep_2010" "concep_2011" "concep_2012" "concep_2013"
## [21] "maternal_age" "any_smoker" "smokeSH" "mean_cpss"
## [25] "mean_epsd" "male" "days_to_peapod"
# fit.npb4 <- npb(niter = 5000, nburn = 2500, X = X.scaled, Y = Y, W = W.scaled2[,-c(4:6)],
# scaleY = TRUE,
# priors = priors.npb, interact = TRUE, XWinteract = TRUE)
# save(fit.npb4, file = here::here("Results", "NPB_Adiposity_v4a.2.rdata"))
load(here::here("Results", "NPB_Adiposity_v4a.2.rdata"))
npb.sum4 <- summary(fit.npb4)
rownames(npb.sum4$main.effects) <- colnames(X.scaled)
npb.sum4$main.effects
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## mean_pm -0.010729658 0.05655652 -0.16237261 0.08479285 0.2704
## mean_o3 -0.026837965 0.08139926 -0.25192835 0.07785339 0.3452
## mean_temp -0.021281728 0.07047256 -0.23587895 0.06986070 0.3164
## pct_tree_cover -0.008791935 0.05659104 -0.15881790 0.10628675 0.2860
## pct_impervious -0.013974122 0.05455793 -0.16094311 0.05231081 0.2728
## mean_aadt_intensity 0.013137539 0.06718301 -0.07642895 0.24337509 0.2544
## dist_m_tri -0.009996501 0.05598899 -0.15666476 0.10753410 0.2852
## dist_m_npl -0.004519011 0.05142667 -0.12632889 0.11463303 0.2480
## dist_m_waste_site 0.028700543 0.10128321 -0.08273024 0.37373023 0.2940
## dist_m_major_emit 0.003127463 0.05741171 -0.10783720 0.16639638 0.2512
## dist_m_cafo -0.017787169 0.10566942 -0.23902691 0.11942903 0.3220
## dist_m_mine_well -0.034101657 0.08603236 -0.27396469 0.06547282 0.3768
## cvd_rate_adj -0.023228803 0.07073171 -0.23038729 0.06134876 0.3300
## res_rate_adj -0.026657334 0.06897587 -0.22825010 0.02910509 0.3124
## violent_crime_rate -0.013739604 0.05881846 -0.16237261 0.07345125 0.3004
## property_crime_rate -0.060386776 0.10487118 -0.35042634 0.01751900 0.4640
## pct_less_hs -0.021194253 0.07087443 -0.22560588 0.07172877 0.3128
## pct_unemp -0.042408868 0.09237638 -0.31381585 0.02807945 0.3704
## pct_limited_eng 0.001753679 0.06262165 -0.10926476 0.16105352 0.2532
## pct_hh_pov -0.024603132 0.06953043 -0.22759937 0.04145441 0.3176
## pct_poc -0.005529783 0.05921470 -0.14275717 0.13180881 0.2752
rownames(npb.sum4$covariates)[2:nrow(npb.sum4$covariates)] <- colnames(W.scaled2[,-c(4:6)])
npb.sum4$covariates
## Posterior Mean SD 95% CI Lower 95% CI Upper
## <NA> 9.05696027 1.7090041 5.5532051 12.38976120
## lat 0.01331768 2.4285093 -4.5763447 4.83704176
## lon 0.24790275 1.1551853 -2.0634598 2.46734397
## lat_lon_int -0.01034163 2.9035509 -5.5991808 5.78744941
## ed_no_hs 1.09237139 0.6338985 -0.1861778 2.32674258
## ed_hs 0.92901957 0.5591388 -0.1605771 2.05000124
## ed_aa 0.76001788 0.4864143 -0.1777218 1.73676996
## ed_4yr 0.14152539 0.4251688 -0.6973512 0.96750477
## low_bmi -0.38333928 0.8043686 -1.9470203 1.17210885
## ovwt_bmi 0.48027457 0.3329607 -0.1748352 1.11760301
## obese_bmi 1.26304562 0.3911199 0.4875585 2.05824324
## concep_spring 0.29437702 0.4125748 -0.5203063 1.08996729
## concep_summer 0.01515875 0.4405620 -0.8502949 0.87134808
## concep_fall -0.08560724 0.4214656 -0.9261968 0.72370831
## concep_2010 0.32198596 1.6905518 -3.1360689 3.75364240
## concep_2011 -0.18794080 1.6787274 -3.5794045 3.10549940
## concep_2012 -0.48301839 1.6755007 -3.7966260 2.84522702
## concep_2013 -0.21253494 1.6837527 -3.5800173 3.21714810
## maternal_age 0.78197359 0.1860804 0.4042412 1.13801734
## any_smoker -0.79021098 0.5216846 -1.7536760 0.28061703
## smokeSH -0.06542164 0.3613893 -0.7652809 0.63362631
## mean_cpss -0.04105702 0.1651580 -0.3558533 0.28371988
## mean_epsd -0.21398096 0.1632124 -0.5421086 0.09665157
## male -1.37308945 0.2733693 -1.9159768 -0.83344562
## days_to_peapod 0.83677467 0.1409503 0.5704070 1.11285878
Next, all of the interactions between exposures or between exposures and covariates
npb.sum4$interactions
## Posterior Mean SD 95% CI Lower 95% CI Upper PIP
## [1,] -0.00048119137 0.008045223 0.000000000 0 0.0104
## [2,] -0.00048702126 0.007029269 0.000000000 0 0.0116
## [3,] -0.00166674994 0.013658238 0.000000000 0 0.0196
## [4,] -0.00545531586 0.028924389 -0.089444959 0 0.0492
## [5,] -0.00063978078 0.008083385 0.000000000 0 0.0124
## [6,] -0.00106386287 0.011198299 0.000000000 0 0.0132
## [7,] -0.00148451058 0.013047494 0.000000000 0 0.0188
## [8,] -0.00798112481 0.037860238 -0.129016543 0 0.0612
## [9,] -0.00503666985 0.028284795 -0.082627134 0 0.0436
## [10,] -0.00243106959 0.017397353 -0.007968193 0 0.0256
## [11,] -0.00322652731 0.021766631 -0.042412585 0 0.0336
## [12,] -0.00198905414 0.016471919 0.000000000 0 0.0208
## [13,] -0.00080887744 0.010125656 0.000000000 0 0.0132
## [14,] -0.00209805479 0.017962448 0.000000000 0 0.0208
## [15,] -0.00130335268 0.011314406 0.000000000 0 0.0196
## [16,] -0.00393736380 0.025383067 -0.062857502 0 0.0384
## [17,] -0.00391637364 0.025791544 -0.062482524 0 0.0340
## [18,] -0.00665111849 0.034529992 -0.120563494 0 0.0516
## [19,] -0.00156704349 0.013393877 0.000000000 0 0.0200
## [20,] -0.00223178575 0.017832880 0.000000000 0 0.0244
## [21,] -0.00616446901 0.031653243 -0.106168283 0 0.0536
## [22,] -0.00095746249 0.010861597 0.000000000 0 0.0168
## [23,] -0.00106672676 0.010111521 0.000000000 0 0.0152
## [24,] -0.00043380763 0.007687657 0.000000000 0 0.0104
## [25,] -0.00330673048 0.022986647 -0.041692982 0 0.0300
## [26,] -0.00169112518 0.013328089 0.000000000 0 0.0216
## [27,] -0.00266749914 0.017629197 -0.038554235 0 0.0312
## [28,] -0.00111251582 0.011619953 0.000000000 0 0.0156
## [29,] -0.00314114621 0.020694758 -0.040843430 0 0.0320
## [30,] -0.00127803795 0.014083809 0.000000000 0 0.0184
## [31,] -0.00055167486 0.008095716 0.000000000 0 0.0064
## [32,] -0.00022067807 0.006236603 0.000000000 0 0.0068
## [33,] -0.00052228589 0.007846151 0.000000000 0 0.0104
## [34,] -0.00046687549 0.006470770 0.000000000 0 0.0092
## [35,] -0.00223577820 0.017190672 0.000000000 0 0.0240
## [36,] -0.00162267170 0.014210316 0.000000000 0 0.0188
## [37,] -0.00135850103 0.011600191 0.000000000 0 0.0180
## [38,] -0.00063774385 0.007484484 0.000000000 0 0.0108
## [39,] -0.00305904677 0.021602985 -0.035015132 0 0.0296
## [40,] -0.00064215330 0.008290627 0.000000000 0 0.0128
## [41,] -0.00108647256 0.010890353 0.000000000 0 0.0152
## [42,] -0.00016161878 0.008763390 0.000000000 0 0.0088
## [43,] -0.00159739669 0.012831776 0.000000000 0 0.0232
## [44,] -0.00111530614 0.011510480 0.000000000 0 0.0164
## [45,] -0.00136154401 0.012123788 0.000000000 0 0.0228
## [46,] -0.00112940505 0.009976262 0.000000000 0 0.0168
## [47,] -0.00236456070 0.018254241 -0.011586402 0 0.0268
## [48,] -0.00281347363 0.019363813 -0.035702531 0 0.0292
## [49,] -0.00107120497 0.010508715 0.000000000 0 0.0148
## [50,] -0.00070284499 0.008698293 0.000000000 0 0.0144
## [51,] -0.00163494019 0.015871695 0.000000000 0 0.0184
## [52,] -0.00121729707 0.013231609 0.000000000 0 0.0164
## [53,] -0.00209653825 0.017716454 0.000000000 0 0.0228
## [54,] -0.00207048029 0.015686749 0.000000000 0 0.0248
## [55,] -0.00282072117 0.019633017 -0.044336193 0 0.0316
## [56,] -0.00083687014 0.008865907 0.000000000 0 0.0148
## [57,] -0.00321623485 0.021304747 -0.045579620 0 0.0324
## [58,] -0.00117665805 0.011101265 0.000000000 0 0.0172
## [59,] -0.00047078243 0.009781310 0.000000000 0 0.0084
## [60,] -0.00106936952 0.010258957 0.000000000 0 0.0152
## [61,] -0.00075482852 0.008402263 0.000000000 0 0.0172
## [62,] -0.00103871141 0.010635414 0.000000000 0 0.0152
## [63,] -0.00062566824 0.009277051 0.000000000 0 0.0124
## [64,] -0.00126127976 0.011342378 0.000000000 0 0.0172
## [65,] -0.00117435339 0.013255278 0.000000000 0 0.0184
## [66,] -0.00207830013 0.016058767 0.000000000 0 0.0252
## [67,] -0.00152938371 0.015176283 0.000000000 0 0.0216
## [68,] -0.00174929216 0.014680046 0.000000000 0 0.0200
## [69,] -0.00073407921 0.007066986 0.000000000 0 0.0144
## [70,] -0.00142337669 0.013421386 0.000000000 0 0.0180
## [71,] -0.00131574470 0.011826562 0.000000000 0 0.0176
## [72,] -0.00196727876 0.017445287 0.000000000 0 0.0228
## [73,] -0.00122053270 0.010597472 0.000000000 0 0.0200
## [74,] -0.00176756736 0.016584402 0.000000000 0 0.0176
## [75,] -0.00040203809 0.005318216 0.000000000 0 0.0092
## [76,] -0.00012499360 0.003254648 0.000000000 0 0.0044
## [77,] -0.00031718812 0.006586439 0.000000000 0 0.0116
## [78,] -0.00040347670 0.007725723 0.000000000 0 0.0124
## [79,] -0.00049912169 0.006653816 0.000000000 0 0.0088
## [80,] -0.00115523483 0.010469052 0.000000000 0 0.0172
## [81,] -0.00130074315 0.011473337 0.000000000 0 0.0180
## [82,] -0.00355501581 0.023985758 -0.047528371 0 0.0340
## [83,] -0.00365877830 0.023899600 -0.054469842 0 0.0356
## [84,] -0.00065489680 0.008089709 0.000000000 0 0.0100
## [85,] -0.00079373845 0.009239640 0.000000000 0 0.0124
## [86,] -0.00128427482 0.013323573 0.000000000 0 0.0144
## [87,] -0.00173269527 0.013630379 0.000000000 0 0.0236
## [88,] -0.00119208718 0.012381720 0.000000000 0 0.0176
## [89,] -0.00106476604 0.010597580 0.000000000 0 0.0148
## [90,] -0.00196064596 0.015878805 0.000000000 0 0.0220
## [91,] -0.00070102441 0.008446909 0.000000000 0 0.0136
## [92,] -0.00134110936 0.012548314 0.000000000 0 0.0164
## [93,] -0.00055311063 0.008441298 0.000000000 0 0.0128
## [94,] -0.00203743703 0.016837928 0.000000000 0 0.0244
## [95,] -0.00055749168 0.007406562 0.000000000 0 0.0104
## [96,] -0.00088360637 0.009865961 0.000000000 0 0.0128
## [97,] -0.00374995083 0.025020803 -0.060725998 0 0.0344
## [98,] -0.00275286678 0.020316391 -0.031429941 0 0.0292
## [99,] -0.00167653267 0.014232033 0.000000000 0 0.0200
## [100,] -0.00077880136 0.008852247 0.000000000 0 0.0112
## [101,] -0.00197944553 0.015666485 0.000000000 0 0.0244
## [102,] -0.00264459558 0.019018776 -0.030658588 0 0.0296
## [103,] -0.00202863236 0.015102265 0.000000000 0 0.0252
## [104,] -0.00134598418 0.012655776 0.000000000 0 0.0176
## [105,] -0.00257336579 0.020104491 -0.004233735 0 0.0260
## [106,] -0.00111349765 0.010196071 0.000000000 0 0.0184
## [107,] -0.00120658025 0.011681921 0.000000000 0 0.0160
## [108,] -0.00137568414 0.012131322 0.000000000 0 0.0200
## [109,] -0.00066382374 0.008491290 0.000000000 0 0.0120
## [110,] -0.00085199394 0.010274077 0.000000000 0 0.0140
## [111,] -0.00038979006 0.009610007 0.000000000 0 0.0104
## [112,] -0.00042667377 0.010049687 0.000000000 0 0.0128
## [113,] -0.00178114635 0.014027483 0.000000000 0 0.0228
## [114,] -0.00166408765 0.012561413 0.000000000 0 0.0232
## [115,] -0.00038912340 0.010674033 0.000000000 0 0.0128
## [116,] -0.00017997952 0.010250138 0.000000000 0 0.0100
## [117,] -0.00070360894 0.008848909 0.000000000 0 0.0108
## [118,] -0.00053618906 0.007767070 0.000000000 0 0.0112
## [119,] -0.00057424933 0.006847186 0.000000000 0 0.0088
## [120,] -0.00114439535 0.011498584 0.000000000 0 0.0176
## [121,] -0.00142418012 0.011948992 0.000000000 0 0.0192
## [122,] -0.00049454926 0.006595541 0.000000000 0 0.0072
## [123,] -0.00143767653 0.012829492 0.000000000 0 0.0180
## [124,] -0.00050749997 0.005801418 0.000000000 0 0.0100
## [125,] -0.00044014558 0.005830674 0.000000000 0 0.0104
## [126,] -0.00144688189 0.012245021 0.000000000 0 0.0196
## [127,] -0.00091148796 0.010044174 0.000000000 0 0.0144
## [128,] -0.00155929895 0.012943446 0.000000000 0 0.0208
## [129,] -0.00088771310 0.008880729 0.000000000 0 0.0160
## [130,] -0.00144787159 0.014031648 0.000000000 0 0.0156
## [131,] -0.00096505437 0.009637861 0.000000000 0 0.0148
## [132,] -0.00144699790 0.014903628 0.000000000 0 0.0172
## [133,] -0.00106178464 0.009983805 0.000000000 0 0.0156
## [134,] -0.00011112840 0.010799270 0.000000000 0 0.0120
## [135,] -0.00152238233 0.014783037 0.000000000 0 0.0152
## [136,] -0.00134681948 0.013331676 0.000000000 0 0.0180
## [137,] -0.00200137368 0.016473061 0.000000000 0 0.0220
## [138,] -0.00208180941 0.015579692 0.000000000 0 0.0240
## [139,] -0.00150884751 0.014504889 0.000000000 0 0.0180
## [140,] -0.00322693555 0.022153251 -0.037703473 0 0.0332
## [141,] -0.00106314694 0.011241589 0.000000000 0 0.0168
## [142,] -0.00144940076 0.015377180 0.000000000 0 0.0224
## [143,] -0.00145808258 0.012963879 0.000000000 0 0.0208
## [144,] -0.00217625710 0.016818853 0.000000000 0 0.0256
## [145,] 0.00033255844 0.014056456 0.000000000 0 0.0096
## [146,] -0.00032958397 0.008531010 0.000000000 0 0.0080
## [147,] -0.00076059986 0.010689670 0.000000000 0 0.0120
## [148,] -0.00092454363 0.009491366 0.000000000 0 0.0136
## [149,] -0.00187594657 0.014614749 0.000000000 0 0.0236
## [150,] -0.00056218002 0.007924094 0.000000000 0 0.0108
## [151,] -0.00431436677 0.025858850 -0.069081109 0 0.0384
## [152,] -0.00384163865 0.024003655 -0.062040346 0 0.0368
## [153,] -0.00214341041 0.015934972 0.000000000 0 0.0228
## [154,] -0.00112098203 0.010770427 0.000000000 0 0.0148
## [155,] -0.00446098788 0.027988261 -0.071207346 0 0.0388
## [156,] -0.00249750710 0.018499422 -0.026498567 0 0.0280
## [157,] -0.00088818720 0.009542892 0.000000000 0 0.0152
## [158,] -0.00127383649 0.012881631 0.000000000 0 0.0172
## [159,] -0.00115763919 0.012552316 0.000000000 0 0.0160
## [160,] -0.00055989090 0.005952226 0.000000000 0 0.0124
## [161,] -0.00157496730 0.013465544 0.000000000 0 0.0216
## [162,] -0.00122147370 0.011554921 0.000000000 0 0.0176
## [163,] -0.00109556534 0.011088799 0.000000000 0 0.0176
## [164,] -0.00151312890 0.014387954 0.000000000 0 0.0172
## [165,] -0.00159635809 0.013740078 0.000000000 0 0.0188
## [166,] -0.00062912825 0.007647930 0.000000000 0 0.0092
## [167,] -0.00034456086 0.004858128 0.000000000 0 0.0084
## [168,] -0.00104725535 0.014327509 0.000000000 0 0.0168
## [169,] -0.00069242705 0.008277534 0.000000000 0 0.0116
## [170,] -0.00061234025 0.008248770 0.000000000 0 0.0088
## [171,] -0.00044268910 0.006513296 0.000000000 0 0.0112
## [172,] -0.00109593195 0.012250346 0.000000000 0 0.0144
## [173,] -0.00050978385 0.007446950 0.000000000 0 0.0108
## [174,] -0.00141088532 0.013394442 0.000000000 0 0.0172
## [175,] -0.00606425395 0.028954381 -0.102536813 0 0.0580
## [176,] -0.00094173443 0.009135336 0.000000000 0 0.0148
## [177,] -0.00131181271 0.011122195 0.000000000 0 0.0172
## [178,] -0.00244401594 0.018482602 -0.021557928 0 0.0284
## [179,] -0.01004791095 0.048229214 -0.167118444 0 0.0644
## [180,] -0.00160587954 0.014568637 0.000000000 0 0.0184
## [181,] -0.00305446849 0.019838172 -0.046404402 0 0.0324
## [182,] -0.00275718616 0.018875758 -0.040281363 0 0.0324
## [183,] -0.00045212020 0.007238453 0.000000000 0 0.0108
## [184,] -0.00055583168 0.006133616 0.000000000 0 0.0104
## [185,] -0.00223306286 0.017595701 0.000000000 0 0.0244
## [186,] -0.00309025764 0.021130537 -0.033790029 0 0.0312
## [187,] -0.00141726938 0.013510251 0.000000000 0 0.0168
## [188,] -0.00147338549 0.013359487 0.000000000 0 0.0192
## [189,] -0.00317301253 0.022709658 -0.037703473 0 0.0312
## [190,] -0.00011056270 0.002089656 0.000000000 0 0.0040
## [191,] -0.00021735278 0.004443447 0.000000000 0 0.0052
## [192,] -0.00040076807 0.005301057 0.000000000 0 0.0100
## [193,] -0.00004548791 0.009949754 0.000000000 0 0.0088
## [194,] -0.00010897094 0.002450297 0.000000000 0 0.0032
## [195,] -0.00039562917 0.004911095 0.000000000 0 0.0108
## [196,] 0.00002659254 0.011718507 0.000000000 0 0.0112
## [197,] -0.00035588810 0.006685672 0.000000000 0 0.0112
## [198,] -0.00034933844 0.005152686 0.000000000 0 0.0076
## [199,] -0.00052423708 0.007968884 0.000000000 0 0.0100
## [200,] -0.00072458655 0.008391609 0.000000000 0 0.0140
## [201,] -0.00189669456 0.015449819 0.000000000 0 0.0256
## [202,] -0.00052564562 0.006854389 0.000000000 0 0.0100
## [203,] -0.00081398941 0.008390644 0.000000000 0 0.0136
## [204,] -0.00139214455 0.012257549 0.000000000 0 0.0216
## [205,] -0.00194583675 0.014709121 0.000000000 0 0.0228
## [206,] -0.00138429982 0.012204624 0.000000000 0 0.0188
## [207,] -0.00242803362 0.016208250 -0.043383508 0 0.0316
## [208,] -0.00063823370 0.006429334 0.000000000 0 0.0128
## [209,] -0.00063660986 0.007209222 0.000000000 0 0.0120
## [210,] -0.00146649476 0.012517313 0.000000000 0 0.0204
## [211,] -0.00062447807 0.010128843 0.000000000 0 0.0112
## [212,] -0.00195750219 0.015248827 0.000000000 0 0.0232
## [213,] -0.00325267778 0.021091406 -0.048242624 0 0.0340
## [214,] -0.00127440201 0.013935458 0.000000000 0 0.0160
## [215,] -0.00219204846 0.018894209 0.000000000 0 0.0204
## [216,] -0.00365276690 0.022789158 -0.060867478 0 0.0356
## [217,] -0.00112606489 0.024808410 0.000000000 0 0.0212
## [218,] -0.00167036511 0.021984190 0.000000000 0 0.0188
## [219,] -0.00413689662 0.027559354 -0.057617580 0 0.0340
## [220,] -0.00130947299 0.012206572 0.000000000 0 0.0172
## [221,] -0.00104886880 0.011208266 0.000000000 0 0.0164
## [222,] -0.00230359629 0.020745660 0.000000000 0 0.0232
## [223,] -0.00324038543 0.020954285 -0.052861889 0 0.0348
## [224,] -0.00174641421 0.015392542 0.000000000 0 0.0220
## [225,] -0.00176030564 0.016683220 0.000000000 0 0.0176
## [226,] -0.00093773581 0.032683800 0.000000000 0 0.0232
## [227,] -0.00211432966 0.018452870 0.000000000 0 0.0256
## [228,] -0.00388804531 0.023341755 -0.065897446 0 0.0376
## [229,] -0.00165789979 0.017211096 0.000000000 0 0.0172
## [230,] -0.00124245579 0.013401347 0.000000000 0 0.0168
## [231,] -0.00095400701 0.009965187 0.000000000 0 0.0148
## [232,] -0.00080381516 0.008134868 0.000000000 0 0.0156
## [233,] -0.00136803747 0.013915083 0.000000000 0 0.0168
## [234,] -0.00208292192 0.016482797 0.000000000 0 0.0228
## [235,] -0.00049846478 0.007929676 0.000000000 0 0.0116
## [236,] -0.00424660029 0.025282151 -0.071234693 0 0.0408
## [237,] -0.00754611739 0.037453386 -0.118463091 0 0.0576
## [238,] -0.00139083305 0.011889523 0.000000000 0 0.0204
## [239,] -0.00149683630 0.012776315 0.000000000 0 0.0192
## [240,] -0.00425161965 0.035740249 -0.046749503 0 0.0320
## [241,] -0.00099782850 0.021164667 0.000000000 0 0.0192
## [242,] -0.00089090492 0.025906122 0.000000000 0 0.0172
## [243,] -0.00067793645 0.012237398 0.000000000 0 0.0124
## [244,] -0.00365445977 0.031121335 -0.036584014 0 0.0308
## [245,] -0.01029181703 0.085609900 -0.095906027 0 0.0432
## [246,] -0.00161642983 0.014370750 0.000000000 0 0.0208
## [247,] -0.00184196026 0.018023922 0.000000000 0 0.0184
## [248,] -0.00307168226 0.026339764 -0.003513201 0 0.0252
## [249,] -0.00243821642 0.019396591 0.000000000 0 0.0248
## [250,] -0.00154915290 0.013072465 0.000000000 0 0.0212
## [251,] -0.00084334558 0.010356643 0.000000000 0 0.0140
## [252,] -0.00056665495 0.008385674 0.000000000 0 0.0128
## [253,] -0.00184514502 0.016269487 0.000000000 0 0.0204
## [254,] -0.00464389738 0.032356177 -0.070617503 0 0.0384
## [255,] -0.00072919160 0.008144194 0.000000000 0 0.0108
## [256,] -0.00148680011 0.012383285 0.000000000 0 0.0204
## [257,] -0.00401691024 0.026032302 -0.062857502 0 0.0344
## [258,] -0.00193625725 0.015236351 0.000000000 0 0.0212
## [259,] -0.00032256350 0.004926483 0.000000000 0 0.0080
## [260,] -0.00574503017 0.031352637 -0.096723591 0 0.0484
## [261,] -0.00540666225 0.033705730 -0.086573922 0 0.0420
## [262,] -0.00177221915 0.019193525 0.000000000 0 0.0200
## [263,] -0.00256066728 0.020450008 -0.022736964 0 0.0296
## [264,] -0.00229952590 0.017544141 -0.029612714 0 0.0288
## [265,] -0.00188030623 0.015311711 0.000000000 0 0.0228
## [266,] -0.00207182675 0.024003845 0.000000000 0 0.0172
## [267,] -0.00091949781 0.009772104 0.000000000 0 0.0152
## [268,] -0.00438454433 0.032903156 -0.062148370 0 0.0348
## [269,] -0.00648406621 0.082012174 -0.030647289 0 0.0304
## [270,] -0.00114167009 0.010968360 0.000000000 0 0.0184
## [271,] -0.00118483178 0.018980707 0.000000000 0 0.0164
## [272,] -0.00333819698 0.026146381 -0.027436855 0 0.0300
## [273,] -0.00232964203 0.018649430 0.000000000 0 0.0248
## [274,] -0.00167880127 0.014861947 0.000000000 0 0.0188
## [275,] -0.00137111171 0.013417825 0.000000000 0 0.0192
## [276,] -0.00062767336 0.007707092 0.000000000 0 0.0132
## [277,] -0.00177861390 0.015191569 0.000000000 0 0.0220
## [278,] -0.00257403084 0.021354794 -0.006151404 0 0.0260
## [279,] -0.00064961379 0.007154437 0.000000000 0 0.0116
## [280,] -0.00113253736 0.011424636 0.000000000 0 0.0152
## [281,] -0.00267800713 0.019853375 -0.020294414 0 0.0260
## [282,] -0.00147664124 0.012383405 0.000000000 0 0.0204
## [283,] -0.00112909558 0.011845918 0.000000000 0 0.0168
## [284,] -0.00097475159 0.010279195 0.000000000 0 0.0156
## [285,] -0.00141267088 0.011849544 0.000000000 0 0.0188
## [286,] -0.00217532397 0.018648668 0.000000000 0 0.0212
## [287,] -0.00227296627 0.019226774 0.000000000 0 0.0224
## [288,] -0.00061717438 0.013995340 0.000000000 0 0.0140
## [289,] -0.00106126557 0.010618237 0.000000000 0 0.0172
## [290,] -0.00327372954 0.027974883 -0.034079190 0 0.0288
## [291,] -0.00224274495 0.016651350 -0.025164400 0 0.0288
## [292,] -0.00184009308 0.014273939 0.000000000 0 0.0212
## [293,] -0.00025944625 0.020037357 0.000000000 0 0.0112
## [294,] -0.00249068422 0.021678936 0.000000000 0 0.0244
## [295,] -0.00154417961 0.012852217 0.000000000 0 0.0244
## [296,] -0.00105648286 0.012011822 0.000000000 0 0.0188
## [297,] -0.00132911072 0.012095000 0.000000000 0 0.0188
## [298,] -0.00363944268 0.026174101 -0.053677926 0 0.0324
## [299,] -0.00081823761 0.012548807 0.000000000 0 0.0144
## [300,] -0.00182488697 0.013728720 0.000000000 0 0.0236
## [301,] -0.00163617374 0.014522488 0.000000000 0 0.0188
## [302,] -0.00134346433 0.011651834 0.000000000 0 0.0200
## [303,] -0.00085311414 0.008689603 0.000000000 0 0.0144
## [304,] -0.00121527078 0.010876990 0.000000000 0 0.0176
## [305,] -0.00100259169 0.012578262 0.000000000 0 0.0156
## [306,] -0.00193637624 0.017947446 0.000000000 0 0.0224
## [307,] -0.00116115011 0.010843176 0.000000000 0 0.0164
## [308,] -0.00122843266 0.011126415 0.000000000 0 0.0160
## [309,] -0.00099085949 0.011503257 0.000000000 0 0.0140
## [310,] -0.00135549867 0.013885584 0.000000000 0 0.0176
## [311,] -0.00153955910 0.013868893 0.000000000 0 0.0196
## [312,] -0.00177071536 0.014012868 0.000000000 0 0.0224
## [313,] -0.00125783969 0.011751109 0.000000000 0 0.0172
## [314,] -0.00213028154 0.019613075 0.000000000 0 0.0200
## [315,] -0.00165509153 0.014346693 0.000000000 0 0.0196
## [316,] -0.00157521121 0.013093334 0.000000000 0 0.0204
## [317,] -0.00171091524 0.016829211 0.000000000 0 0.0208
## [318,] -0.00239938330 0.020331722 0.000000000 0 0.0216
## [319,] -0.00088730807 0.009458436 0.000000000 0 0.0136
## [320,] -0.00119913103 0.015703699 0.000000000 0 0.0192
## [321,] -0.00139865295 0.012494480 0.000000000 0 0.0192
## [322,] -0.00198967664 0.016470489 0.000000000 0 0.0232
## [323,] -0.00262514974 0.019684724 -0.032167606 0 0.0296
## [324,] -0.00437661559 0.025986886 -0.071208582 0 0.0392
## [325,] -0.00260661837 0.019374092 -0.007086615 0 0.0256
## [326,] -0.00209517154 0.017383762 0.000000000 0 0.0232
## [327,] -0.00262279539 0.021431896 -0.002586799 0 0.0256
## [328,] -0.00114715669 0.013183757 0.000000000 0 0.0164
## [329,] -0.00529756190 0.030690945 -0.091620298 0 0.0448
## [330,] -0.00144763447 0.014487613 0.000000000 0 0.0184
## [331,] -0.00164786850 0.015233426 0.000000000 0 0.0196
## [332,] -0.00335762674 0.021111443 -0.058558380 0 0.0352
## [333,] -0.00113602094 0.011664828 0.000000000 0 0.0144
## [334,] -0.00112224910 0.012060459 0.000000000 0 0.0152
## [335,] -0.00229247846 0.018405704 0.000000000 0 0.0252
## [336,] -0.00154919180 0.013301588 0.000000000 0 0.0200
## [337,] -0.00034293220 0.010073528 0.000000000 0 0.0144
## [338,] -0.00185447683 0.021225240 0.000000000 0 0.0252
## [339,] -0.00103721986 0.011338134 0.000000000 0 0.0136
## [340,] -0.00203209122 0.018094595 0.000000000 0 0.0228
## [341,] -0.00024427541 0.013356435 0.000000000 0 0.0132
## [342,] -0.00124590811 0.013303652 0.000000000 0 0.0156
## [343,] -0.00199150562 0.019475739 0.000000000 0 0.0220
## [344,] -0.00198049427 0.014756866 0.000000000 0 0.0256
## [345,] -0.00119384661 0.010694123 0.000000000 0 0.0196
## [346,] -0.00122630816 0.013113718 0.000000000 0 0.0204
## [347,] -0.00172893567 0.014002285 0.000000000 0 0.0232
## [348,] -0.00202978895 0.017595371 0.000000000 0 0.0216
## [349,] -0.00160555187 0.014678974 0.000000000 0 0.0204
## [350,] -0.00227444303 0.017315766 -0.014641013 0 0.0276
## [351,] -0.00058266856 0.007762347 0.000000000 0 0.0108
## [352,] -0.00078392559 0.008156482 0.000000000 0 0.0112
## [353,] -0.00133940757 0.013094350 0.000000000 0 0.0192
## [354,] -0.00175917041 0.013337494 0.000000000 0 0.0236
## [355,] -0.00107419335 0.011045092 0.000000000 0 0.0172
## [356,] -0.00127792691 0.012102227 0.000000000 0 0.0192
## [357,] -0.00111820672 0.010855063 0.000000000 0 0.0164
## [358,] -0.00103033400 0.009882865 0.000000000 0 0.0184
## [359,] -0.00232202952 0.024558477 0.000000000 0 0.0224
## [360,] -0.00255753154 0.025272957 0.000000000 0 0.0208
## [361,] -0.00158415829 0.013700065 0.000000000 0 0.0188
## [362,] -0.00189308221 0.018302975 0.000000000 0 0.0176
## [363,] -0.00184819120 0.018141484 0.000000000 0 0.0192
## [364,] -0.00202033350 0.018999501 0.000000000 0 0.0184
## [365,] -0.00308157180 0.023690144 -0.026187423 0 0.0268
## [366,] -0.00208011260 0.017408739 0.000000000 0 0.0220
## [367,] -0.00107881064 0.010772796 0.000000000 0 0.0140
## [368,] -0.00154907308 0.015713689 0.000000000 0 0.0172
## [369,] -0.00212137758 0.016685871 0.000000000 0 0.0236
## [370,] -0.00128781296 0.013004153 0.000000000 0 0.0156
## [371,] -0.00170314511 0.016262384 0.000000000 0 0.0224
## [372,] -0.00075885198 0.008746684 0.000000000 0 0.0148
## [373,] -0.00162587967 0.016767382 0.000000000 0 0.0188
## [374,] -0.00111710483 0.013153366 0.000000000 0 0.0176
## [375,] -0.00112358722 0.010216745 0.000000000 0 0.0188
## [376,] -0.00149528650 0.013737251 0.000000000 0 0.0200
## [377,] -0.00056389697 0.011034673 0.000000000 0 0.0140
## [378,] -0.00164596093 0.014742463 0.000000000 0 0.0176
## [379,] -0.00275886298 0.019243407 -0.035473102 0 0.0296
## [380,] -0.00224686218 0.015706891 -0.021145304 0 0.0264
## [381,] -0.00083055753 0.010174216 0.000000000 0 0.0116
## [382,] -0.00092107992 0.014400010 0.000000000 0 0.0140
## [383,] -0.00141207481 0.013503621 0.000000000 0 0.0208
## [384,] -0.00176261725 0.014066475 0.000000000 0 0.0220
## [385,] -0.00189740814 0.016342998 0.000000000 0 0.0228
## [386,] -0.00323364267 0.024797573 -0.030687472 0 0.0296
## [387,] -0.00090961681 0.010803729 0.000000000 0 0.0132
## [388,] -0.00201853946 0.015784725 0.000000000 0 0.0256
## [389,] -0.00162830083 0.018757607 0.000000000 0 0.0180
## [390,] -0.00191140822 0.016305056 0.000000000 0 0.0200
## [391,] -0.00132142020 0.012058781 0.000000000 0 0.0176
## [392,] -0.00205626370 0.017578645 0.000000000 0 0.0232
## [393,] -0.00095919088 0.014461731 0.000000000 0 0.0192
## [394,] -0.00142210053 0.013300755 0.000000000 0 0.0220
## [395,] -0.00025284140 0.019513636 0.000000000 0 0.0108
## [396,] -0.00061398295 0.009311815 0.000000000 0 0.0088
## [397,] -0.00100582864 0.014580377 0.000000000 0 0.0196
## [398,] -0.00204038539 0.017194912 0.000000000 0 0.0236
## [399,] -0.00096130451 0.010025488 0.000000000 0 0.0152
## [400,] -0.00211358914 0.015587022 0.000000000 0 0.0252
## [401,] -0.00082145124 0.009450098 0.000000000 0 0.0128
## [402,] -0.00115445101 0.011113421 0.000000000 0 0.0164
## [403,] -0.00776320391 0.039455547 -0.129185355 0 0.0536
## [404,] -0.00200975563 0.015635290 0.000000000 0 0.0240
## [405,] -0.00014609650 0.008826730 0.000000000 0 0.0096
## [406,] -0.00102979542 0.012597800 0.000000000 0 0.0172
## [407,] -0.00134886493 0.014087291 0.000000000 0 0.0148
## [408,] -0.00115791801 0.017834617 0.000000000 0 0.0176
## [409,] -0.00131789170 0.015693808 0.000000000 0 0.0196
## [410,] -0.00243323597 0.026440967 0.000000000 0 0.0244
## [411,] -0.00188699782 0.016087996 0.000000000 0 0.0248
## [412,] -0.00165628618 0.014468806 0.000000000 0 0.0200
## [413,] -0.00076056904 0.013823059 0.000000000 0 0.0168
## [414,] -0.00110024955 0.014118111 0.000000000 0 0.0128
## [415,] -0.00095973542 0.010176185 0.000000000 0 0.0168
## [416,] -0.00165448362 0.014949049 0.000000000 0 0.0196
## [417,] -0.00103261425 0.011026294 0.000000000 0 0.0140
## [418,] -0.00226716788 0.018029442 0.000000000 0 0.0240
## [419,] -0.00048296306 0.012922511 0.000000000 0 0.0128
## [420,] -0.00080712965 0.009487229 0.000000000 0 0.0136
## [421,] -0.00064973662 0.030781034 0.000000000 0 0.0180
## [422,] -0.00124249404 0.013629392 0.000000000 0 0.0164
## [423,] -0.00039349996 0.005507358 0.000000000 0 0.0084
## [424,] -0.00055620260 0.006414278 0.000000000 0 0.0096
## [425,] -0.00080822928 0.009814490 0.000000000 0 0.0120
## [426,] -0.00057691840 0.007395103 0.000000000 0 0.0116
## [427,] -0.00567469692 0.027239587 -0.099444909 0 0.0540
## [428,] -0.00352120012 0.021943206 -0.061586836 0 0.0356
## [429,] -0.00042176959 0.007511449 0.000000000 0 0.0076
## [430,] -0.00178930047 0.014023964 0.000000000 0 0.0236
## [431,] -0.00133724079 0.013511214 0.000000000 0 0.0164
## [432,] -0.00132523670 0.012289253 0.000000000 0 0.0200
## [433,] -0.00160646232 0.016566152 0.000000000 0 0.0188
## [434,] -0.00165440988 0.018247563 0.000000000 0 0.0208
## [435,] -0.00059082020 0.014116851 0.000000000 0 0.0104
## [436,] -0.00103663531 0.010040846 0.000000000 0 0.0152
## [437,] -0.00142502282 0.011855618 0.000000000 0 0.0208
## [438,] -0.00202577171 0.018484544 0.000000000 0 0.0200
## [439,] -0.00183623435 0.015662918 0.000000000 0 0.0216
## [440,] -0.00115108573 0.013478682 0.000000000 0 0.0164
## [441,] -0.00152733015 0.014074599 0.000000000 0 0.0176
## [442,] -0.00129295554 0.011754694 0.000000000 0 0.0184
## [443,] -0.00049692169 0.011337432 0.000000000 0 0.0136
## [444,] -0.00101358380 0.009906846 0.000000000 0 0.0136
## [445,] -0.00145162595 0.014785171 0.000000000 0 0.0200
## [446,] -0.00117721516 0.011776754 0.000000000 0 0.0156
## [447,] -0.00042085083 0.006721851 0.000000000 0 0.0104
## [448,] -0.00095235263 0.009808455 0.000000000 0 0.0168
## [449,] -0.00099554306 0.012227310 0.000000000 0 0.0164
## [450,] -0.00105832942 0.011170902 0.000000000 0 0.0172
## [451,] -0.00041270479 0.006851289 0.000000000 0 0.0128
## [452,] -0.00089807288 0.010136023 0.000000000 0 0.0128
## [453,] -0.00191832386 0.014158526 -0.013033120 0 0.0256
## [454,] 0.00008741716 0.041173449 0.000000000 0 0.0152
## [455,] -0.00373139074 0.032696868 -0.032585204 0 0.0280
## [456,] -0.00173043712 0.016091182 0.000000000 0 0.0220
## [457,] -0.00145970103 0.013071254 0.000000000 0 0.0184
## [458,] -0.00404841652 0.061583965 -0.033415519 0 0.0276
## [459,] -0.00169851049 0.014996586 0.000000000 0 0.0212
## [460,] -0.00196372248 0.016385499 0.000000000 0 0.0244
## [461,] -0.00119708331 0.010683171 0.000000000 0 0.0176
## [462,] -0.00225703945 0.017732359 0.000000000 0 0.0240
## [463,] -0.00104913657 0.010906621 0.000000000 0 0.0172
## [464,] -0.00174096521 0.016351479 0.000000000 0 0.0200
## [465,] 0.00017317257 0.028670921 0.000000000 0 0.0144
## [466,] -0.00267999749 0.021185510 -0.008395487 0 0.0260
## [467,] -0.00209651098 0.018814808 0.000000000 0 0.0244
## [468,] -0.00199347832 0.015337811 0.000000000 0 0.0244
## [469,] -0.00091204417 0.040073078 0.000000000 0 0.0216
## [470,] -0.00150155139 0.013914310 0.000000000 0 0.0168
## [471,] -0.00211102812 0.015017084 -0.021868400 0 0.0284
## [472,] -0.00093288362 0.009968489 0.000000000 0 0.0164
## [473,] -0.00201277238 0.017180475 -0.001290447 0 0.0260
## [474,] -0.00146924528 0.013117812 0.000000000 0 0.0196
## [475,] -0.00089170485 0.008862399 0.000000000 0 0.0160
## [476,] -0.00068491190 0.007246489 0.000000000 0 0.0116
## [477,] -0.00109268286 0.010660108 0.000000000 0 0.0176
## [478,] -0.00142281068 0.014242435 0.000000000 0 0.0160
## [479,] -0.00285330448 0.022462658 -0.033202933 0 0.0312
## [480,] -0.00071697740 0.009290817 0.000000000 0 0.0116
## [481,] -0.00149459646 0.012909020 0.000000000 0 0.0180
## [482,] -0.00136673994 0.011867109 0.000000000 0 0.0216
## [483,] -0.00257564142 0.020194943 0.000000000 0 0.0252
## [484,] -0.00293125118 0.020955782 -0.032167817 0 0.0296
## [485,] -0.00242850303 0.019694995 0.000000000 0 0.0224
## [486,] -0.00366242623 0.026922753 -0.049308392 0 0.0332
## [487,] -0.00091877906 0.016412214 0.000000000 0 0.0148
## [488,] -0.00086636846 0.010256908 0.000000000 0 0.0140
## [489,] -0.00129448287 0.011697734 0.000000000 0 0.0188
## [490,] -0.00400164765 0.026822479 -0.058651850 0 0.0356
## [491,] -0.00222028341 0.020810018 0.000000000 0 0.0244
## [492,] -0.00136213468 0.011055623 0.000000000 0 0.0212
## [493,] -0.00108274943 0.020500409 0.000000000 0 0.0196
## [494,] -0.00116815160 0.015277734 0.000000000 0 0.0148
## [495,] -0.00185013591 0.015124072 0.000000000 0 0.0228
## [496,] -0.00089243411 0.009231829 0.000000000 0 0.0140
## [497,] -0.00205496449 0.018578736 0.000000000 0 0.0208
## [498,] -0.00099130055 0.010952271 0.000000000 0 0.0164
## [499,] -0.00131607949 0.013066273 0.000000000 0 0.0164
## [500,] -0.00207580166 0.017286580 0.000000000 0 0.0224
## [501,] -0.00159734430 0.012448707 0.000000000 0 0.0208
## [502,] -0.00235816165 0.017532618 0.000000000 0 0.0240
## [503,] -0.00211989146 0.018802478 0.000000000 0 0.0232
## [504,] -0.00059745979 0.013126859 0.000000000 0 0.0128
## [505,] -0.00164952554 0.015171462 0.000000000 0 0.0196
## [506,] -0.00229119100 0.021942233 0.000000000 0 0.0240
## [507,] -0.00048672834 0.017400081 0.000000000 0 0.0176
## [508,] -0.00214080475 0.016432885 0.000000000 0 0.0248
## [509,] -0.00203822866 0.018893656 0.000000000 0 0.0228
## [510,] -0.00130072985 0.011930990 0.000000000 0 0.0176
## [511,] -0.00267283859 0.019355110 -0.031070980 0 0.0276
## [512,] -0.00230645530 0.019278231 0.000000000 0 0.0208
## [513,] -0.00163919146 0.013612375 0.000000000 0 0.0196
## [514,] -0.00159260584 0.016685865 0.000000000 0 0.0216
## [515,] -0.00261483245 0.019861337 -0.015475137 0 0.0268
## [516,] -0.00134453614 0.012765002 0.000000000 0 0.0156
## [517,] -0.00214103712 0.019549327 0.000000000 0 0.0256
## [518,] -0.00290653015 0.024736705 -0.019444903 0 0.0276
## [519,] -0.00170173502 0.013761423 0.000000000 0 0.0232
## [520,] -0.00117302394 0.010032485 0.000000000 0 0.0184
## [521,] -0.00169422974 0.013783258 0.000000000 0 0.0200
## [522,] -0.00514569495 0.030077480 -0.093532745 0 0.0392
## [523,] -0.00128033277 0.011787741 0.000000000 0 0.0196
## [524,] -0.00129530778 0.012096559 0.000000000 0 0.0192
## [525,] -0.00195901271 0.016269323 0.000000000 0 0.0248
## [526,] -0.00226662146 0.019711992 0.000000000 0 0.0244
## [527,] -0.00183499285 0.016801366 0.000000000 0 0.0208
## [528,] -0.00054203905 0.011721260 0.000000000 0 0.0136
## [529,] -0.00252543194 0.020760346 -0.020817738 0 0.0272
## [530,] -0.00167225076 0.016197126 0.000000000 0 0.0180
## [531,] 0.00013477831 0.016476856 0.000000000 0 0.0116
## [532,] -0.00190677198 0.016144615 0.000000000 0 0.0232
## [533,] -0.00185224304 0.017671938 0.000000000 0 0.0204
## [534,] -0.00220261699 0.016449528 -0.031218309 0 0.0288
## [535,] -0.00157596485 0.016216576 0.000000000 0 0.0196
## [536,] -0.00275494848 0.019724345 -0.029280559 0 0.0304
## [537,] -0.00104649985 0.010916198 0.000000000 0 0.0140
## [538,] -0.00118394283 0.011533062 0.000000000 0 0.0160
## [539,] -0.00237377865 0.017441107 -0.014917515 0 0.0264
## [540,] -0.00244443919 0.018058430 -0.007086615 0 0.0256
## [541,] -0.00211774132 0.017790910 0.000000000 0 0.0208
## [542,] -0.00235306132 0.019753031 -0.013344491 0 0.0268
## [543,] -0.00108775565 0.011140797 0.000000000 0 0.0168
## [544,] -0.00178408349 0.013994612 0.000000000 0 0.0216
## [545,] -0.00246789557 0.018369057 -0.025877812 0 0.0280
## [546,] -0.00572193015 0.033093324 -0.090816748 0 0.0432
## [547,] -0.00120162501 0.011882926 0.000000000 0 0.0176
## [548,] -0.00721302156 0.033840049 -0.124174890 0 0.0612
## [549,] -0.00431709761 0.027997211 -0.061449842 0 0.0356
## [550,] -0.00246654521 0.024941150 0.000000000 0 0.0220
## [551,] -0.00132695094 0.013006843 0.000000000 0 0.0152
## [552,] -0.00206960517 0.018005621 0.000000000 0 0.0240
## [553,] -0.00327002247 0.023866221 -0.034969077 0 0.0288
## [554,] -0.00281469372 0.039988114 0.000000000 0 0.0216
## [555,] -0.00122510584 0.019814101 0.000000000 0 0.0200
## [556,] -0.00097897249 0.010258888 0.000000000 0 0.0148
## [557,] -0.00285935421 0.023386695 0.000000000 0 0.0232
## [558,] -0.00212106949 0.017741842 -0.019131442 0 0.0276
## [559,] -0.00174914428 0.016469467 0.000000000 0 0.0220
## [560,] -0.00151011633 0.014150324 0.000000000 0 0.0188
## [561,] -0.00354026496 0.032115502 -0.027219724 0 0.0276
## [562,] -0.00148819085 0.014327986 0.000000000 0 0.0196
## [563,] -0.00253401551 0.024003676 0.000000000 0 0.0256
## [564,] -0.00197396347 0.015242318 0.000000000 0 0.0232
## [565,] -0.00260022088 0.019708538 0.000000000 0 0.0244
## [566,] -0.00113939311 0.011918514 0.000000000 0 0.0160
## [567,] -0.00289184099 0.019244241 -0.038168487 0 0.0308
## [568,] -0.00395865532 0.025094125 -0.068952463 0 0.0356
## [569,] -0.00277514274 0.020439110 -0.028645649 0 0.0272
## [570,] -0.00309401446 0.019648364 -0.051676725 0 0.0336
## [571,] -0.00156982733 0.014158729 0.000000000 0 0.0192
## [572,] -0.00127633642 0.012303285 0.000000000 0 0.0184
## [573,] -0.00151110294 0.013149747 0.000000000 0 0.0216
## [574,] -0.00163424351 0.017088552 0.000000000 0 0.0184
## [575,] -0.00170573609 0.020986399 0.000000000 0 0.0204
## [576,] -0.00207382581 0.019104489 0.000000000 0 0.0240
## [577,] -0.00321711674 0.021005148 -0.048508074 0 0.0340
## [578,] -0.00389049535 0.049102805 0.000000000 0 0.0240
## [579,] -0.00190886699 0.015625828 0.000000000 0 0.0204
## [580,] -0.00059904449 0.017169471 0.000000000 0 0.0156
## [581,] -0.00381856284 0.029503421 -0.051486534 0 0.0336
## [582,] -0.00457279095 0.034002415 -0.048585205 0 0.0328
## [583,] -0.00151410448 0.013361719 0.000000000 0 0.0164
## [584,] -0.00199343995 0.015761241 0.000000000 0 0.0228
## [585,] -0.00237611194 0.017770083 -0.009995880 0 0.0260
## [586,] -0.00161017480 0.013730629 0.000000000 0 0.0204
## [587,] -0.00304414880 0.027698675 -0.017839771 0 0.0272
## [588,] -0.00460116629 0.027353808 -0.074403884 0 0.0408
## [589,] -0.00308960629 0.028755014 -0.003944801 0 0.0264
## [590,] -0.00199093585 0.018829748 0.000000000 0 0.0236
## [591,] -0.00518301719 0.031991704 -0.076896086 0 0.0424
## [592,] -0.00342034014 0.022882234 -0.050067850 0 0.0348
## [593,] -0.00294923529 0.022660120 -0.026239090 0 0.0276
## [594,] -0.00284720702 0.022051500 -0.011404877 0 0.0268
## [595,] -0.00138593304 0.013370020 0.000000000 0 0.0216
## [596,] -0.00526230147 0.031846448 -0.081470141 0 0.0428
## [597,] -0.00399274861 0.026553005 -0.062784358 0 0.0368
## [598,] -0.00288192077 0.035078322 0.000000000 0 0.0220
## [599,] -0.00111446120 0.012073254 0.000000000 0 0.0180
## [600,] -0.00166724473 0.017733823 0.000000000 0 0.0176
## [601,] -0.00154951245 0.013868289 0.000000000 0 0.0172
## [602,] -0.00149159931 0.012916873 0.000000000 0 0.0192
## [603,] -0.00061978245 0.013792800 0.000000000 0 0.0148
## [604,] -0.00167525301 0.016509908 0.000000000 0 0.0200
## [605,] -0.00252221789 0.018608595 -0.032649990 0 0.0304
## [606,] -0.00092665733 0.010448469 0.000000000 0 0.0176
## [607,] -0.00275538808 0.019644227 -0.031776000 0 0.0288
## [608,] -0.00119008952 0.014280135 0.000000000 0 0.0200
## [609,] -0.00229584052 0.016494117 -0.025877812 0 0.0280
## [610,] -0.00165894301 0.012351968 0.000000000 0 0.0232
## [611,] -0.00150334198 0.014380522 0.000000000 0 0.0172
## [612,] -0.00083266095 0.009688698 0.000000000 0 0.0132
## [613,] -0.00230672211 0.019634993 0.000000000 0 0.0232
## [614,] -0.00263388833 0.020243890 -0.021617901 0 0.0268
## [615,] -0.00189603104 0.014432426 0.000000000 0 0.0248
## [616,] -0.00144527629 0.013830045 0.000000000 0 0.0192
## [617,] -0.00170053532 0.014621710 0.000000000 0 0.0224
## [618,] -0.00250493759 0.017592111 -0.021224474 0 0.0268
## [619,] -0.00109546631 0.011028798 0.000000000 0 0.0140
## [620,] -0.00292306551 0.021682542 -0.021200346 0 0.0276
## [621,] -0.00211480201 0.017484106 0.000000000 0 0.0240
## [622,] -0.00268287146 0.019356395 -0.033006411 0 0.0292
## [623,] -0.00228958578 0.018638406 0.000000000 0 0.0264
## [624,] -0.00116502658 0.013146405 0.000000000 0 0.0164
## [625,] -0.00380697675 0.027592428 -0.048875897 0 0.0336
## [626,] -0.00208820120 0.016606256 0.000000000 0 0.0212
## [627,] -0.00107201172 0.016511179 0.000000000 0 0.0164
## [628,] -0.00165090182 0.014483010 0.000000000 0 0.0208
## [629,] -0.00436859709 0.038445543 -0.044380882 0 0.0344
## [630,] -0.00176428094 0.016268684 0.000000000 0 0.0220
## [631,] -0.00188606908 0.016179771 0.000000000 0 0.0196
## [632,] -0.00214854062 0.016416958 0.000000000 0 0.0252
## [633,] -0.00236898182 0.017459860 0.000000000 0 0.0232
## [634,] -0.00143486738 0.013197803 0.000000000 0 0.0188
## [635,] -0.00181214899 0.019457166 0.000000000 0 0.0212
## [636,] -0.00147866102 0.012490484 0.000000000 0 0.0196
## [637,] -0.00341157020 0.029211622 -0.032385440 0 0.0280
## [638,] -0.00248444947 0.020274788 0.000000000 0 0.0236
## [639,] -0.00179998552 0.014639412 0.000000000 0 0.0208
## [640,] -0.00116791694 0.010924227 0.000000000 0 0.0188
## [641,] -0.00443585435 0.030272189 -0.055935412 0 0.0352
## [642,] -0.00382575534 0.023669909 -0.059860983 0 0.0396
## [643,] -0.00127622506 0.013611424 0.000000000 0 0.0136
## [644,] -0.00405354816 0.026354089 -0.062647867 0 0.0336
## [645,] -0.00227521512 0.018189124 0.000000000 0 0.0244
## [646,] -0.00208390084 0.015563957 -0.013509518 0 0.0272
## [647,] -0.00085190876 0.009492997 0.000000000 0 0.0128
## [648,] -0.00145461188 0.014695583 0.000000000 0 0.0184
## [649,] -0.00113459948 0.011365716 0.000000000 0 0.0204
## [650,] -0.00213269416 0.017081027 0.000000000 0 0.0204
## [651,] -0.00083279051 0.009305455 0.000000000 0 0.0140
## [652,] -0.00063441528 0.013326402 0.000000000 0 0.0136
## [653,] -0.00239601608 0.020556473 -0.014379893 0 0.0264
## [654,] -0.00130905350 0.013854010 0.000000000 0 0.0172
## [655,] -0.00110282953 0.011011849 0.000000000 0 0.0136
## [656,] -0.00083550548 0.016387311 0.000000000 0 0.0132
## [657,] -0.00174620941 0.015824471 0.000000000 0 0.0172
## [658,] -0.00134441660 0.013102996 0.000000000 0 0.0188
## [659,] -0.00206025271 0.018231867 0.000000000 0 0.0200
## [660,] -0.00153727349 0.014064347 0.000000000 0 0.0204
## [661,] -0.00261284838 0.020652608 -0.024360252 0 0.0272
## [662,] -0.00139461299 0.010676269 0.000000000 0 0.0216
## [663,] -0.00173358012 0.014244273 0.000000000 0 0.0216
## [664,] -0.00071029924 0.008786051 0.000000000 0 0.0116
## [665,] -0.00173383551 0.015568045 0.000000000 0 0.0204
## [666,] -0.00179280134 0.015760184 0.000000000 0 0.0228
## [667,] -0.00120789526 0.012724637 0.000000000 0 0.0180
## [668,] -0.00285326867 0.019795421 -0.038349982 0 0.0284
## [669,] -0.00240456655 0.020517498 0.000000000 0 0.0228
## [670,] -0.00233098927 0.018802880 0.000000000 0 0.0236
## [671,] -0.00144873534 0.012512066 0.000000000 0 0.0196
## [672,] -0.00162160390 0.013440288 0.000000000 0 0.0244
## [673,] -0.00159688104 0.015809480 0.000000000 0 0.0212
## [674,] -0.00252490953 0.019754665 -0.028795728 0 0.0284
## [675,] -0.00082687906 0.008963115 0.000000000 0 0.0140
## [676,] -0.00084457847 0.010011871 0.000000000 0 0.0152
## [677,] -0.00193206621 0.016400310 0.000000000 0 0.0228
## [678,] -0.00155947716 0.013741649 0.000000000 0 0.0208
## [679,] -0.00294403065 0.022454101 -0.021815892 0 0.0280
## [680,] -0.00209000513 0.019487588 0.000000000 0 0.0244
## [681,] -0.00213420964 0.017476269 0.000000000 0 0.0228
## [682,] -0.00095526267 0.010816389 0.000000000 0 0.0176
## [683,] -0.00205626027 0.015543067 0.000000000 0 0.0248
## [684,] -0.00110853113 0.010328979 0.000000000 0 0.0172
## [685,] -0.00242527161 0.025079297 0.000000000 0 0.0252
## [686,] -0.00136083117 0.012218031 0.000000000 0 0.0188
## [687,] -0.00290518686 0.019687206 -0.043782692 0 0.0296
## [688,] -0.00225613927 0.017804357 0.000000000 0 0.0244
## [689,] -0.00350993669 0.025312849 -0.041051562 0 0.0280
## [690,] -0.00474115669 0.030491634 -0.070227870 0 0.0408
## [691,] -0.00085850923 0.009330100 0.000000000 0 0.0148
## [692,] -0.00293139965 0.019901881 -0.036489883 0 0.0284
## [693,] -0.00230119307 0.018613455 0.000000000 0 0.0236
## [694,] -0.00360758594 0.032042388 -0.035702531 0 0.0300
## [695,] -0.00153751596 0.014940602 0.000000000 0 0.0200
## [696,] -0.00118483769 0.012940051 0.000000000 0 0.0160
## [697,] -0.00132900114 0.012502399 0.000000000 0 0.0200
## [698,] -0.00185745250 0.037649980 0.000000000 0 0.0204
## [699,] -0.00073628831 0.008541453 0.000000000 0 0.0124
## [700,] -0.00185840025 0.018428784 0.000000000 0 0.0180
## [701,] -0.00345492628 0.030569414 -0.020786599 0 0.0292
## [702,] 0.00024092563 0.026823887 0.000000000 0 0.0176
## [703,] -0.00198113632 0.016219654 0.000000000 0 0.0248
## [704,] -0.00098065978 0.012097749 0.000000000 0 0.0156
## [705,] -0.00176462847 0.017002212 0.000000000 0 0.0216
## [706,] -0.00127266598 0.013055069 0.000000000 0 0.0184
## [707,] -0.00208265351 0.015532531 -0.004198962 0 0.0272
## [708,] -0.00126459912 0.011347460 0.000000000 0 0.0160
## [709,] -0.00348040559 0.049559008 -0.009563184 0 0.0268
## [710,] -0.00187968484 0.014173136 0.000000000 0 0.0228
## [711,] -0.00128407689 0.011284334 0.000000000 0 0.0196
## [712,] -0.00214307349 0.015418050 -0.009810182 0 0.0260
## [713,] -0.00284893621 0.020974023 -0.020655030 0 0.0268
## [714,] -0.00272767710 0.018302132 -0.040609288 0 0.0312
None of the exposures had a PIP > 0.5. Here I’m going to loop through some linear regression models to see if anything shows up here. Remember that the exposure and covariates have all been scaled.
lm_results <- data.frame()
for(i in 1:length(colnames(X.scaled))) {
lm_df <- as.data.frame(cbind(Y, X.scaled[,i], W.scaled2))
names(lm_df)[2] <- colnames(X.scaled)[i]
ad_lm <- lm(adiposity ~ ., data = lm_df)
temp <- data.frame(exp = colnames(X.scaled)[i],
beta = summary(ad_lm)$coefficients[2,1],
beta.se = summary(ad_lm)$coefficients[2,2],
p.value = summary(ad_lm)$coefficients[2,4])
temp$lcl <- temp$beta - 1.96*temp$beta.se
temp$ucl <- temp$beta + 1.96*temp$beta.se
lm_results <- bind_rows(lm_results, temp)
rm(temp)
}
lm_results
write_csv(lm_results, here::here("Results", "LM_Effects_Adiposity_v4.csv"))
lm_df <- as.data.frame(cbind(Y, X.scaled, W.scaled2))
ad_waste_lm <- lm(adiposity ~ dist_m_waste_site +
lat + lon + lat_lon_int +
latina_re + black_re + other_re +
ed_no_hs + ed_hs + ed_aa + ed_4yr +
low_bmi + ovwt_bmi + obese_bmi +
concep_spring + concep_summer + concep_fall +
concep_2010 + concep_2011 + concep_2012 + concep_2013 +
maternal_age + any_smoker + smokeSH +
mean_cpss + mean_epsd + male + days_to_peapod,
data = lm_df)
summary(ad_waste_lm)
##
## Call:
## lm(formula = adiposity ~ dist_m_waste_site + lat + lon + lat_lon_int +
## latina_re + black_re + other_re + ed_no_hs + ed_hs + ed_aa +
## ed_4yr + low_bmi + ovwt_bmi + obese_bmi + concep_spring +
## concep_summer + concep_fall + concep_2010 + concep_2011 +
## concep_2012 + concep_2013 + maternal_age + any_smoker + smokeSH +
## mean_cpss + mean_epsd + male + days_to_peapod, data = lm_df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.1152 -2.6385 -0.1678 2.7592 15.5462
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.02150 3.90254 2.568 0.0104 *
## dist_m_waste_site 0.36281 0.15149 2.395 0.0169 *
## lat 12.72052 148.21325 0.086 0.9316
## lon -5.73270 70.63195 -0.081 0.9353
## lat_lon_int 15.09494 178.21522 0.085 0.9325
## latina_re -0.48057 0.40192 -1.196 0.2322
## black_re -0.27689 0.43874 -0.631 0.5282
## other_re -0.87609 0.57642 -1.520 0.1290
## ed_no_hs 1.23866 0.65067 1.904 0.0573 .
## ed_hs 1.07560 0.58154 1.850 0.0648 .
## ed_aa 0.81041 0.51063 1.587 0.1129
## ed_4yr 0.07400 0.42583 0.174 0.8621
## low_bmi -0.42315 0.80718 -0.524 0.6003
## ovwt_bmi 0.52044 0.34122 1.525 0.1276
## obese_bmi 1.24425 0.38806 3.206 0.0014 **
## concep_spring 0.29517 0.39971 0.738 0.4605
## concep_summer 0.13378 0.39414 0.339 0.7344
## concep_fall 0.03868 0.39069 0.099 0.9212
## concep_2010 -0.55100 3.90233 -0.141 0.8878
## concep_2011 -1.11020 3.90475 -0.284 0.7762
## concep_2012 -1.36997 3.89964 -0.351 0.7255
## concep_2013 -1.04232 3.90481 -0.267 0.7896
## maternal_age 0.79576 0.18829 4.226 0.00002669215 ***
## any_smoker -0.88965 0.53394 -1.666 0.0961 .
## smokeSH -0.09976 0.37929 -0.263 0.7926
## mean_cpss -0.06078 0.16639 -0.365 0.7150
## mean_epsd -0.19513 0.16928 -1.153 0.2494
## male -1.37099 0.27394 -5.005 0.00000069768 ***
## days_to_peapod 0.82688 0.13914 5.943 0.00000000429 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.773 on 751 degrees of freedom
## Multiple R-squared: 0.1402, Adjusted R-squared: 0.1082
## F-statistic: 4.375 on 28 and 751 DF, p-value: 0.000000000001403
plot(ad_waste_lm)
## Warning: not plotting observations with leverage one:
## 1
lm_df <- as.data.frame(cbind(Y, X.scaled, W.scaled2))
ad_res_lm <- lm(adiposity ~ res_rate_adj +
lat + lon + lat_lon_int +
latina_re + black_re + other_re +
ed_no_hs + ed_hs + ed_aa + ed_4yr +
low_bmi + ovwt_bmi + obese_bmi +
concep_spring + concep_summer + concep_fall +
concep_2010 + concep_2011 + concep_2012 + concep_2013 +
maternal_age + any_smoker + smokeSH +
mean_cpss + mean_epsd + male + days_to_peapod,
data = lm_df)
summary(ad_res_lm)
##
## Call:
## lm(formula = adiposity ~ res_rate_adj + lat + lon + lat_lon_int +
## latina_re + black_re + other_re + ed_no_hs + ed_hs + ed_aa +
## ed_4yr + low_bmi + ovwt_bmi + obese_bmi + concep_spring +
## concep_summer + concep_fall + concep_2010 + concep_2011 +
## concep_2012 + concep_2013 + maternal_age + any_smoker + smokeSH +
## mean_cpss + mean_epsd + male + days_to_peapod, data = lm_df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.7234 -2.5753 -0.2042 2.7269 16.1631
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.67278 3.90877 2.475 0.01356 *
## res_rate_adj -0.24964 0.15140 -1.649 0.09960 .
## lat 36.76972 148.72945 0.247 0.80480
## lon -17.28087 70.88017 -0.244 0.80745
## lat_lon_int 44.14802 178.83348 0.247 0.80508
## latina_re -0.38383 0.40356 -0.951 0.34185
## black_re -0.19174 0.43981 -0.436 0.66298
## other_re -0.81865 0.57851 -1.415 0.15746
## ed_no_hs 1.31937 0.65663 2.009 0.04486 *
## ed_hs 1.15845 0.58646 1.975 0.04860 *
## ed_aa 0.94161 0.51282 1.836 0.06673 .
## ed_4yr 0.13362 0.42564 0.314 0.75367
## low_bmi -0.50970 0.80895 -0.630 0.52884
## ovwt_bmi 0.47288 0.34205 1.382 0.16723
## obese_bmi 1.26674 0.38909 3.256 0.00118 **
## concep_spring 0.31816 0.40032 0.795 0.42700
## concep_summer 0.11014 0.39513 0.279 0.78053
## concep_fall 0.04729 0.39147 0.121 0.90387
## concep_2010 -0.33604 3.90881 -0.086 0.93151
## concep_2011 -0.86851 3.91105 -0.222 0.82432
## concep_2012 -1.16914 3.90637 -0.299 0.76480
## concep_2013 -0.83812 3.91148 -0.214 0.83039
## maternal_age 0.76831 0.18806 4.086 0.00004870493 ***
## any_smoker -0.86685 0.53535 -1.619 0.10582
## smokeSH -0.09518 0.38007 -0.250 0.80233
## mean_cpss -0.04247 0.16639 -0.255 0.79861
## mean_epsd -0.19821 0.16980 -1.167 0.24346
## male -1.32203 0.27511 -4.805 0.00000186532 ***
## days_to_peapod 0.82938 0.13942 5.949 0.00000000414 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.781 on 751 degrees of freedom
## Multiple R-squared: 0.1368, Adjusted R-squared: 0.1046
## F-statistic: 4.251 on 28 and 751 DF, p-value: 0.000000000004589
plot(ad_res_lm)
## Warning: not plotting observations with leverage one:
## 1
lm_df <- as.data.frame(cbind(Y, X.scaled, W.scaled2))
ad_pcrime_lm <- lm(adiposity ~ property_crime_rate +
lat + lon + lat_lon_int +
latina_re + black_re + other_re +
ed_no_hs + ed_hs + ed_aa + ed_4yr +
low_bmi + ovwt_bmi + obese_bmi +
concep_spring + concep_summer + concep_fall +
concep_2010 + concep_2011 + concep_2012 + concep_2013 +
maternal_age + any_smoker + smokeSH +
mean_cpss + mean_epsd + male + days_to_peapod,
data = lm_df)
summary(ad_pcrime_lm)
##
## Call:
## lm(formula = adiposity ~ property_crime_rate + lat + lon + lat_lon_int +
## latina_re + black_re + other_re + ed_no_hs + ed_hs + ed_aa +
## ed_4yr + low_bmi + ovwt_bmi + obese_bmi + concep_spring +
## concep_summer + concep_fall + concep_2010 + concep_2011 +
## concep_2012 + concep_2013 + maternal_age + any_smoker + smokeSH +
## mean_cpss + mean_epsd + male + days_to_peapod, data = lm_df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.6783 -2.6161 -0.1684 2.7626 15.8124
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.65291 3.90266 2.473 0.01360 *
## property_crime_rate -0.31479 0.13972 -2.253 0.02455 *
## lat 31.91270 148.29287 0.215 0.82967
## lon -14.93929 70.67019 -0.211 0.83264
## lat_lon_int 38.29701 178.30884 0.215 0.83000
## latina_re -0.46827 0.40192 -1.165 0.24435
## black_re -0.29343 0.43940 -0.668 0.50446
## other_re -0.93457 0.57731 -1.619 0.10590
## ed_no_hs 1.19286 0.65058 1.834 0.06712 .
## ed_hs 1.07542 0.58181 1.848 0.06494 .
## ed_aa 0.91635 0.51063 1.795 0.07313 .
## ed_4yr 0.18710 0.42523 0.440 0.66007
## low_bmi -0.46686 0.80730 -0.578 0.56324
## ovwt_bmi 0.46817 0.34145 1.371 0.17074
## obese_bmi 1.25965 0.38829 3.244 0.00123 **
## concep_spring 0.32470 0.39966 0.812 0.41680
## concep_summer 0.14151 0.39434 0.359 0.71980
## concep_fall 0.02365 0.39096 0.060 0.95179
## concep_2010 -0.18066 3.90305 -0.046 0.96309
## concep_2011 -0.71684 3.90537 -0.184 0.85441
## concep_2012 -1.03992 3.90058 -0.267 0.78984
## concep_2013 -0.72418 3.90556 -0.185 0.85295
## maternal_age 0.77043 0.18770 4.104 0.00004496165 ***
## any_smoker -0.86307 0.53440 -1.615 0.10672
## smokeSH -0.10116 0.37946 -0.267 0.78985
## mean_cpss -0.03802 0.16586 -0.229 0.81874
## mean_epsd -0.20551 0.16917 -1.215 0.22481
## male -1.40426 0.27486 -5.109 0.00000041128 ***
## days_to_peapod 0.82385 0.13921 5.918 0.00000000495 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.775 on 751 degrees of freedom
## Multiple R-squared: 0.1395, Adjusted R-squared: 0.1074
## F-statistic: 4.348 on 28 and 751 DF, p-value: 0.000000000001819
plot(ad_pcrime_lm)
## Warning: not plotting observations with leverage one:
## 1
lm_df <- as.data.frame(cbind(Y, X.scaled, W.scaled2))
ad_unemp_lm <- lm(adiposity ~ pct_unemp +
lat + lon + lat_lon_int +
latina_re + black_re + other_re +
ed_no_hs + ed_hs + ed_aa + ed_4yr +
low_bmi + ovwt_bmi + obese_bmi +
concep_spring + concep_summer + concep_fall +
concep_2010 + concep_2011 + concep_2012 + concep_2013 +
maternal_age + any_smoker + smokeSH +
mean_cpss + mean_epsd + male + days_to_peapod,
data = lm_df)
summary(ad_unemp_lm)
##
## Call:
## lm(formula = adiposity ~ pct_unemp + lat + lon + lat_lon_int +
## latina_re + black_re + other_re + ed_no_hs + ed_hs + ed_aa +
## ed_4yr + low_bmi + ovwt_bmi + obese_bmi + concep_spring +
## concep_summer + concep_fall + concep_2010 + concep_2011 +
## concep_2012 + concep_2013 + maternal_age + any_smoker + smokeSH +
## mean_cpss + mean_epsd + male + days_to_peapod, data = lm_df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.6136 -2.5739 -0.1227 2.6643 15.9796
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.66018 3.90718 2.472 0.013641 *
## pct_unemp -0.27813 0.15209 -1.829 0.067843 .
## lat 18.84591 148.40739 0.127 0.898984
## lon -8.68304 70.72418 -0.123 0.902319
## lat_lon_int 22.61179 178.44698 0.127 0.899200
## latina_re -0.29709 0.40929 -0.726 0.468151
## black_re -0.09939 0.44480 -0.223 0.823243
## other_re -0.80122 0.57866 -1.385 0.166583
## ed_no_hs 1.32492 0.65577 2.020 0.043695 *
## ed_hs 1.19286 0.58775 2.030 0.042755 *
## ed_aa 0.97771 0.51414 1.902 0.057602 .
## ed_4yr 0.19854 0.42625 0.466 0.641502
## low_bmi -0.41917 0.80868 -0.518 0.604377
## ovwt_bmi 0.48223 0.34170 1.411 0.158581
## obese_bmi 1.29104 0.38955 3.314 0.000963 ***
## concep_spring 0.29460 0.40051 0.736 0.462232
## concep_summer 0.11011 0.39493 0.279 0.780471
## concep_fall 0.04963 0.39131 0.127 0.899106
## concep_2010 -0.39542 3.90747 -0.101 0.919421
## concep_2011 -0.91640 3.90959 -0.234 0.814740
## concep_2012 -1.21936 3.90492 -0.312 0.754928
## concep_2013 -0.85571 3.90990 -0.219 0.826821
## maternal_age 0.74830 0.18780 3.985 0.00007418007 ***
## any_smoker -0.93043 0.53505 -1.739 0.082455 .
## smokeSH -0.08158 0.38005 -0.215 0.830094
## mean_cpss -0.03983 0.16616 -0.240 0.810619
## mean_epsd -0.19942 0.16960 -1.176 0.240031
## male -1.35414 0.27429 -4.937 0.00000097868 ***
## days_to_peapod 0.83228 0.13939 5.971 0.00000000364 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.779 on 751 degrees of freedom
## Multiple R-squared: 0.1375, Adjusted R-squared: 0.1054
## F-statistic: 4.277 on 28 and 751 DF, p-value: 0.000000000003591
plot(ad_unemp_lm)
## Warning: not plotting observations with leverage one:
## 1